Search Results (59)

Accurate and comprehensive characterization of high-steep slopes is crucial for real-time risk prediction, disaster assessment, and damage evolution monitoring. The study focused on a high-steep rocky slope along the Yanjiang Expressway in Sichuan Province, China. A novel digital reconstruction method was introduced, which integrates terrestrial laser scanning (TLS) and unmanned aerial vehicle (UAV) photogrammetry through a Transformer-based method combining GeoTransformer with the Maximal Cliques (MAC) algorithm. The results indicated that TLS excels in capturing fine-scale features, whereas UAV demonstrates superior performance in large-scale terrain reconstruction. However, multi-sensor data exhibit heterogeneity in terms of partial overlap, large outliers, and density differences. To address these challenges, the GeoTransformer-MAC framework extracts geometrically invariant features from cross-source point cloud (CSPC) to establish initial correspondences, followed by rigorous screening of high-quality locally consistent correspondences to optimize transformation parameters. This method achieves accurate digital reconstruction of the high-steep rock slope. Global and local error analyses verify the model’s superiority in both overall slope characterization and fine-scale feature representation. Compared with the TLS-only model and the conventional method, the Transformer-based method improves the slope model integrity by 85.58%, increases the data density by 9.71%, and improves the accuracy by nearly threefold. This study provides a novel approach for the digital modeling of complex terrains, which serves the refined identification and modeling of geohazards for high-steep slopes in complex mountainous regions. Full article

Backgrounds: High-volume (HV) metastatic castration-sensitive prostate cancer (mCSPC) is an aggressive disease. Despite this, we aimed to assess the metastatic patterns associated with a favorable prognosis in HV disease with bone metastasis (BM), including BM’s coexistence with lung metastasis (LM). Methods: We retrospectively analyzed 379 patients with synchronous mCSPC. They were categorized using the CHAARTED criteria as low-volume (LV) or HV with BM, classified based on extent of the disease from 1 to 4 (HV-EOD1–4) with or without LM. Multivariate Cox models for overall survival and castration-resistance-free survival assessed the prognostic values of HV-EOD1–4 compared with LV disease and the presence of LM. Site-specific radiographic progression at the time of castration-resistant prostate diagnosis was assessed in patients with BM and LM. Results: Multivariate analyses for overall survival showed no prognostic value of HV-EOD1 (hazard ratio [HR] 0.90; 95% confidence interval [CI] 0.43–1.85; p = 0.77), HV-EOD2 (HR 1.17; 95% CI 0.69–1.99; p = 0.57), and LM (HR 1.29; 95% CI 0.80–2.07; p = 0.29). In the analyses, HV-EOD ≤ 2 and LM did not influence castration resistance-free survival. LM showed a significantly lower incidence of radiographic progression to castration-resistant prostate cancer than BM (6.0% vs. 29.9%, p < 0.001). Conclusions: This study indicates the prognostic heterogeneity of HV disease considering BM and LM. These findings may aid in determining the treatment intensity for mCSPC. Full article

This study aims to investigate the role of exogenous spermidine (Spd) in mitigating the adverse effects of cadmium (Cd) stress on the growth and development of cucumber (Cucumis sativus). The cucumber cultivar “Xintaimici” was used as the experimental material, and a hydroponic experiment was carried out. Based on a baseline Cd concentration of 10 mg·L⁻¹, Spd was supplemented at concentrations of 0.05, 0.1, 0.2, 0.4, and 0.5 mM, resulting in seven treatment groups: control group (CK), S0 group (Cd-only treatment, 10 mg·L⁻¹ Cd + 0 mM Spd), S1+ Cd group (10 mg·L⁻¹ Cd + 0.05 mM Spd), S2+ Cd group (10 mg·L⁻¹ Cd + 0.1 mM Spd), S3+ Cd group (10 mg·L⁻¹ Cd + 0.2 mM Spd), S4+ Cd group (10 mg·L⁻¹ Cd + 0.4 mM Spd), and S5+ Cd group (10 mg·L⁻¹ Cd + 0.5 mM Spd). This study analyzed the regulatory effects of Spd on the growth and development, antioxidant capacity and cadmium accumulation characteristics of cucumber seeds and seedlings. It was found that cadmium stress significantly inhibited their growth process and led to a decline in multiple physiological indicators. Under a Cd concentration of 10 mg·L⁻¹, the application of 0.2 mM Spd significantly improved these parameters. During the seedling stage, the application of 0.2 mM Spd under Cd stress significantly enhanced the activities of superoxide dismutase (SOD), peroxidase (POD), catalase (CAT), and ascorbate peroxidase (APX), as well as the content of soluble proteins, while significantly reducing malondialdehyde (MDA) levels. Cd content analysis revealed that 0.2 mM Spd promoted Cd accumulation in roots while suppressing its translocation to young leaves, thereby reducing Cd accumulation in aboveground tissues. Gene expression analysis demonstrated that this treatment significantly upregulated the expression levels of the phytochelatin synthase gene (CsPCS1) and the gene associated with reduced glutathione synthesis (CsGSHS). In conclusion, the exogenous application of 0.2 mM Spd effectively alleviates oxidative damage and osmotic stress induced by Cd stress in cucumber, promotes plant growth, and significantly enhances Cd tolerance. Full article

At diagnosis, metastatic prostate cancer (PC) is sensitive to androgen deprivation therapy (ADT), and patients are usually referred to as having castration-sensitive prostate cancer (mCSPC). The combination of ADT and androgen receptor pathway inhibitors (ARPI) is the current standard of care for mCSPC. This study aimed to review the literature on economic evaluations and health economic models related to mCSPC. A literature search was performed covering Medline, Embase, and Scopus with additional grey literature sources. Studies with data on health economic evaluations focusing on Europe or North America were relevant. 18 peer-reviewed articles and 10 grey literature documents were included. The majority (n = 23) had a deterministic Markov structure and applied either Markov cohort or partitioned survival models. Evaluations investigated various types of ADT-based combinations, comparing the addition of ARPI, chemotherapy agents, or radiation therapy to ADT alone. We concluded that economic evaluations in the field of PC are widely published, and there are a large number of publications even in the specific subgroup of mCSPC. Regardless of the investigated interventions, most studies applied similar methodologies and simulated patients from the mCSPC state until the development of mCRPC or death. Full article

LiDAR-captured 3D point clouds are widely used in self-driving cars and smart cities. Point-based semantic segmentation methods allow for more efficient use of the rich geometric information contained in 3D point clouds, so it has gradually replaced other methods as the mainstream deep learning method in 3D point cloud semantic segmentation. However, existing methods suffer from limited receptive fields and feature misalignment due to hierarchical downsampling. To address these challenges, we propose PSNet, a novel patch-based self-attention network that significantly expands the receptive field while ensuring feature alignment through a patch-aggregation paradigm. PSNet combines patch-based self-attention feature extraction with common point feature aggregation (CPFA) to implicitly model large-scale spatial relationships. The framework first divides the point cloud into overlapping patches to extract local features via multi-head self-attention, then aggregates features of common points across patches to capture long-range context. Extensive experiments on Toronto-3D and Complex Scene Point Cloud (CSPC) datasets validate PSNet’s state-of-the-art performance, achieving overall accuracies (OAs) of 98.4% and 97.2%, respectively, with significant improvements in challenging categories (e.g., +32.1% IoU for fences). Experimental results on the S3DIS dataset show that PSNet attains competitive mIoU accuracy (71.2%) while maintaining lower inference latency (7.03 s). The PSNet architecture achieves a larger receptive field coverage, which represents a significant advantage over existing methods. This work not only reveals the mechanism of patch-based self-attention for receptive field enhancement but also provides insights into attention-based 3D geometric learning and semantic segmentation architectures. Furthermore, it provides substantial references for applications in autonomous vehicle navigation and smart city infrastructure management. Full article

Background: canine distemper (CD) is a highly contagious and fatal disease caused by canine distemper virus (CDV), posing a significant threat to carnivores. New CDV strain circulation and multi-species infection may lead to the potential dilemma of safety concern and insufficient efficacy of the commercial modified live vaccines. Safe and effective vaccines for canine and wildlife prevention of CD need to be continuously updated and developed. Methods: we developed two DNA vaccines, p17F-LNP and p17H-LNP, encoding the fusion protein (F) or hemagglutinin protein (H) of a field CDV strain (HLJ17) and encapsulated in lipid nanoparticles (LNPs). Serum neutralizing antibody (NAb) was evaluated via neutralization tests, and mouse serum cytokine detection were evaluated via ELISA. Results: immunization of p17F-LNP and p17H-LNP monovalent or bivalent were safe, and induced robust CDV NAb and cytokine responses in mice. LNP encapsulation improved immune responses compared to naked DNA formulation, and the bivalent formulation of p17F-LNP and p17H-LNP (p17F/H-LNP) exhibited synergistic effects with a high level of immune responses. Moreover, two doses of p17F/H-LNP induced long-lasting CDV NAb for over 300 days in dogs, and prime and boost NAb responses in foxes and raccoon dogs. Conclusions: the preliminary findings provided here warrant further development of the p17F/H-LNP vaccine for animal targets against CDV infection. Full article

There has been a proliferation of novel treatments for the management of advanced prostate cancer (PCa), including androgen receptor pathway inhibitors (ARPI). Although there are health economic analyses of novel PCa treatments, such as ARPIs for specific health states, there is a lack of sequential analyses. Our paper aims to fill this gap. We developed a Monte Carlo Markov model to simulate the management of advanced PCa to end-of-life. We modeled patients who begin in metastatic and nonmetastatic castration-sensitive PCa (mCSPC and nmCSPC), with risk stratification for mCSPC, progressing to metastatic castration-resistant PCa (mCRPC). Using current guidelines and recent literature, we simulated admissible treatment sequences over these states along a 15-year horizon. We report the best treatment sequences in terms of efficacy and cost-effectiveness. We find that the most cost-effective use of ARPIs is early in advanced PCa for a cost-effectiveness threshold (CET) of CAD 100K per QALY. For a CET of CAD 50K per QALY, early ARPI use is most cost-effective in mCSPC-starting patients but not nmCSPC-starting. We conclude that the most cost-effective way to use ARPIs is when patients first enter advanced PCa. The most cost-effective ARPI at current Canadian prices is abiraterone, mostly due to abiraterone’s lower price level. Full article

Accurate and rapid detection of potato surface defects is crucial for advancing intelligent potato sorting. To elevate detection accuracy as well as shorten the computational load of the model, this paper proposes a lightweight Flaw-YOLOv5s algorithm for potato surface defect detection. Firstly, Depthwise Separable Convolution (DWConv) is used to displace the original Conv in the YOLOv5s network, aiming to reduce computational burden and parameters. Then, the SPPF in the backbone network is replaced by SPPELAN, which combines SPP with ELAN to enable the model to perform multi-scale pooling and feature extraction, optimizing detection capacity for small targets in potatoes. Finally, the lightweight convolution PConv is used to introduce a new structure, CSPC, to substitute for the C3 in the benchmark network, which decreases redundant computations and reduces the model parameters, achieving a lightweight network model. Experimental results demonstrate that the Flaw-YOLOv5s algorithm obtains a mean Average Precision (mAP) of 95.6%, with a precision of 94.6%, representing, respectively, an improvement of 1.6 and 1.8 percentage points over the YOLOv5s network. With only 4.33 million parameters, this lightweight and efficient model satisfies the requirements for detecting surface defects in potatoes. This research provides a reference for the online detection of potato surface defects and deployment on mobile devices. Full article

Background: Evidence to help avoid unnecessary prostate biopsies is being actively pursued. Our goal was to develop and internally validate a nomogram for predicting clinically significant prostate cancer (csPC) in men with low suspicion of disease (prostate specific antigen [PSA] < 10 ng/mL, normal digital rectal examination [DRE]), in whom magnetic resonance imaging (MRI) findings are positive. Methods: Patients with no prior prostate cancer diagnosis who underwent MRI–ultrasound fusion biopsy of the prostate were retrospectively analyzed. Inclusion criteria were PSA < 10 ng/mL, normal DRE, Prostate Imaging Reporting And Data System (PIRADS) category ≥ 3, and no extraprostatic extension or seminal vesicle invasion reported on MRI. Associations between csPC diagnosis and patient or lesion characteristics were analyzed, and a multivariable model was developed. Internal validation of the model with 5-fold cross-validation and bootstrapping methods was performed. Results: Among 209 patients, 67 were diagnosed with csPC. Factors incorporated into the model for predicting csPC were age, 5-alpha reductase inhibitor use, PSA, prostate volume, PIRADS > 3, and lesion location in the peripheral zone. The model’s ROC AUC was 0.86, with consistent performance at internal validation (0.84 with cross-validation, 0.82 with bootstrapping). With an empirical threshold of <10% csPC probability to omit biopsy, 72 (50.7%) unnecessary biopsies would have been avoided, at the cost of missing 2 (3.0%) csPC cases. Conclusions: Our nomogram might serve as a valuable tool in refining selection criteria in men considered for prostate biopsy. The major limitation of the study is its retrospective character. Prospective, external validation of the model is warranted. Full article

Background: Gleason scores of 8 or higher indicate a poorer prognosis in metastatic castration-sensitive prostate cancer (mCSPC). This study aims to perform a systematic review and network meta-analysis (NMA) to compare overall survival (OS) and progression-free survival (PFS) among combination therapies with androgen receptor signaling inhibitors (ARSIs) in mCSPC patients, stratified by Gleason score ≥8 and <8. Methods: A literature search was conducted across PubMed, Embase, and Web of Science, using a PRISMA-guided systematic search strategy, covering January 2013 to June 2024. Results: Twelve studies including 12,652 patients were included in the NMAs. In the overall population, most ARSI combination therapies improved survival outcomes, except for orteronel + androgen deprivation therapy (ADT). In the Gleason score ≥8 subgroup, all ARSI combination therapies improved OS, with rezvilutamide showing the highest probability of being the best treatment for OS (HR 0.48, 95% CI 0.31–0.76, P-scores 0.88). In the Gleason score <8 subgroup, only darolutamide + docetaxel + ADT (HR 0.49, 95% CI 0.29–0.81) and apalutamide + ADT (HR 0.67, 95% CI 0.46–0.98) improved OS. Conclusions: ARSI combination therapy is effective for mCSPC patients with Gleason score ≥8, but further investigation is needed to confirm its efficacy in patients with Gleason score <8. Full article

Unsupervised Domain Adaptation for Object Detection (UDA-OD) aims to adapt a model trained on a labeled source domain to an unlabeled target domain, addressing challenges posed by domain shifts. However, existing methods often face significant challenges, particularly in detecting small objects and over-relying on classification confidence for pseudo-label selection, which often leads to inaccurate bounding box localization. To address these issues, we propose a novel UDA-OD framework that leverages scale consistency (SC) and Temporal Ensemble Pseudo-Label Selection (TEPLS) to enhance cross-domain robustness and detection performance. Specifically, we introduce Cross-Scale Prediction Consistency (CSPC) to enforce consistent detection across multiple resolutions, improving detection robustness for objects of varying scales. Additionally, we integrate Intra-Class Feature Consistency (ICFC), which employs contrastive learning to align feature representations within each class, further enhancing adaptation. To ensure high-quality pseudo-labels, TEPLS combines temporal localization stability with classification confidence, mitigating the impact of noisy predictions and improving both classification and localization accuracy. Extensive experiments on challenging benchmarks, including Cityscapes to Foggy Cityscapes, Sim10k to Cityscapes, and Virtual Mine to Actual Mine, demonstrate that our method achieves state-of-the-art performance, with notable improvements in small object detection and overall cross-domain robustness. These results highlight the effectiveness of our framework in addressing key limitations of existing UDA-OD approaches. Full article

Background: 5-alpha reductase inhibitors (5-ARIs) change hormonal pathways and reduce prostate size. We evaluated the effects of 5-ARIs on prostatic multiparametric magnetic resonance imaging (mpMRI) suspicious findings and in the identification of prostate cancer using targeted biopsies. Methods: We conducted a retrospective study including 600 consecutive patients who, between 2017 and 2021, underwent combined transperineal fusion biopsies. Primary outcomes were Prostate Imaging Reporting and Data System version 2 (PIRADS v2) scores and the identification of clinically significant prostate cancer from suspicious lesions (targeted CSPC). Outcomes were compared between patients treated with 5-ARIs for a minimum of 6 months and the other patients. Results: Patients treated with 5-ARIs were older (p < 0.001) with higher rates of previous prostate biopsies (p = 0.004). PIRADS scores were 3, 4, and 5 in 15 (29%), 28 (54%), and 9 (17%) patients among the 5-ARI group and 130 (24%), 308 (56%), and 110 (20%) patients among the others, and the scores were not different between the groups (p = 0.69). The targeted CSPC identification rate among 5-ARI patients was 31%, not different compared to the non-5-ARI group (p = 1). Rates of targeted CSPC for each PIRADS score were not affected by 5-ARI treatment. The 5-ARI was not associated with neither PIRADS ≥ 4 score nor targeted CSPC on logistic regression analyses (OR = 0.76, 95% CI 0.4–1.4 and OR = 1.02, 95% CI 0.5–1.9, respectively). Conclusions: 5-ARI treatment is not associated with PIRADS score alterations or targeted biopsy results. Patients treated by 5-ARIs with suspicious lesions should not be addressed differently during the mpMRI-related diagnostic process. Full article

Technological advances have dramatically improved precision agriculture, and accurate crop classification is a key aspect of precision agriculture (PA). The flexibility and real-time nature of UAVs have led them to become an important tool for acquiring agricultural data and enabling precise crop classification. Currently, crop identification relies heavily on complex high-precision models that often struggle to provide real-time performance. Research on lightweight models specifically for crop classification is also limited. In this paper, we propose a crop classification method based on UAV visible-light images based on PP-LiteSeg, a lightweight model proposed by Baidu. To improve the accuracy, a pyramid pooling module is designed in this paper, which integrates adaptive mean pooling and CSPC (Convolutional Spatial Pyramid Pooling) techniques to handle high-resolution features. In addition, a sparse self-attention mechanism is employed to help the model pay more attention to locally important semantic regions in the image. The combination of adaptive average pooling and the sparse self-attention mechanism can better handle different levels of contextual information. To train the model, a new dataset based on UAV visible-light images including nine categories such as rice, soybean, red bean, wheat, corn, poplar, etc., with a time span of two years was created for accurate crop classification. The experimental results show that the improved model outperforms other models in terms of accuracy and prediction performance, with a MIoU (mean intersection ratio joint) of 94.79%, which is 2.79% better than the original model. Based on the UAV RGB images demonstrated in this paper, the improved model achieves a better balance between real-time performance and accuracy. In conclusion, the method effectively utilizes UAV RGB data and lightweight deep semantic segmentation models to provide valuable insights for crop classification and UAV field monitoring. Full article

Background/Objectives: Prostate cancer (PC) represents the second most diagnosed form of cancer in men on a global scale. Despite the theranostic efficacy of prostate-specific membrane antigen (PSMA) radioligands, there is a spectrum of PC disease in which PSMA expression is low or absent. The gastrin-releasing peptide receptor (GRPR), also known as the bombesin type 2 receptor, has been identified as a target in both the early and advanced stages of PC. The objective of this study was to prepare and preclinically evaluate [^99mTc]Tc-iPSMA-Bombesin ([^99mTc]Tc-iPSMA-BN), estimate dosimetry in healthy subjects, and assess the diagnostic efficacy of the radiotracer in patients with metastatic PC, with the hypothesis of non-inferiority to one of the gold standards, [¹⁸F]-PSMA-1007. Moreover, the potential of [^99mTc]Tc-iPSMA-BN as a theranostic pair with [¹⁷⁷Lu]Lu-iPSMA-BN was investigated. Methods: [^99mTc]Tc-iPSMA-BN was prepared under GMP conditions with radiochemical purities > 95%, showing specific recognition by PSMA and GRP receptors in prostate cancer cells and mice bearing PC tumors. Six healthy volunteers were enrolled, and [^99mTc]Tc-iPSMA-BN SPECT/CT imaging (740 MBq) was performed to estimate the dosimetry. The pilot clinical study included seven mCRPC and four mCSPC patients with prior androgen deprivation therapy. All patients had a recent [¹⁸F]-PSMA-PET/CT scan and were enrolled in this prospective study on their own signed behalf. Volumetric lesion target-to-background ratios (TBRs) were obtained from PET/CT and SPECT/CT images. Results: [^99mTc]Tc-iPSMA-BN effective radiation dose was 1.94 ± 0.39 mSv/740 MBq. A total of 178 lesions were detected via CT, 162 via [¹⁸F]-PSMA-1007 PET, and 155 via [^99mTc]Tc-iPSMA-BN SPECT. Three patients with mCRPC had higher TBR values on SPECT than on PET. [^99mTc]Tc-iPSMA-BN appears to have better lesion detection in patients with aggressive histologic transformation. Two-way ANOVA analysis revealed a significant difference in TBR values between patients with mCRPC and mCSPC (p < 0.05) but no difference between [¹⁸F]-PSMA-1007 and [^99mTc]Tc-iPSMA-BN (p > 0.05). In one patient, [¹⁷⁷Lu]Lu-iPSMA-BN showed a high correlation with [^99mTc]Tc-iPSMA-BN for lesions that concentrated radioactivity. Conclusions: [^99mTc]Tc-iPSMA-BN SPECT/CT is a promising alternative not only for diagnostic purposes but also for broadening the spectrum of PC patients who may benefit from radionuclide theranostics. The results justify the development of a clinical trial involving a significant number of patients with PC. Full article

Background: The treatment strategy for metastatic castration-sensitive prostate cancer (mCSPC) has changed significantly in recent years. Based on various guidelines, an upfront androgen receptor signaling inhibitor (ARSI) is the first choice, but in patients of Asian descent, including Japanese patients, there are a certain number of cases in which androgen deprivation therapy (ADT) and CAB are more effective. If patients can be identified who show a marked response to ADT within 12 weeks after the initiation of ADT, which is the inclusion criterion for ARSI clinical trials targeting mCSPC, it would be valuable from an economic standpoint. Methods: A total of 218 patients with pure prostate adenocarcinoma and treated with ADT at the Kanazawa University Hospital between January 2000 and December 2020 were included in this study. As a risk classification for mCSPC, in addition to the LATITUDE and CHAARTED criteria, we used the castration-sensitive prostate cancer classification proposed by Kanazawa University (Canazawa), developed by the Department of Urology of Kanazawa University. The Canazawa classification was based on three factors: Gleason pattern 5, bone scan index (BSI) ≥ 1.5, and lactate dehydrogenase (LDH) ≥ 300 IU/L. It defined patients with one factor or less as low-risk and patients with two or three factors as high-risk. The overall survival (OS) and time to castration resistance (TTCR) were estimated retrospectively using the Kaplan–Meier method, and factors associated with TTCR were identified using univariate and multivariate analyses. Results: The median follow-up period was 40.4 months, the median OS period was 85.2 months, and the median TTCR period was 16.4 months. The Canazawa risk classification provided the clearest distinction between the OS and TTCR in mCSPC patients. Multivariate analysis revealed a decrease in PSA levels of <95% at 12 weeks after ADT initiation and was a predictor of short TTCR in low-risk, low-volume patients across all risk classifications. Conclusion: The Canazawa classification differentiated the prognosis of mCSPC patients more clearly. A PSA reduction rate of <95% at 12 w after starting ADT in low-risk, low-volume patients of all risk classifications was significantly shorter than the TTCR. We propose a new treatment strategy, in which patients with low-risk mCSPC are treated with ADT and switched to ARSIs based on the rate of PSA reduction at 12 w. Full article