First-in-human study of PSMA-targeting agent, [18F]AlF-P16-093: dosimetry and initial evaluation in prostate cancer patients.

PURPOSE: This is a first-in-human study to evaluate the radiation dosimetry of a new prostate-specific membrane antigen (PSMA)-targeted radiopharmaceutical, [18F]AlF-P16-093, and also initial investigation of its ability to detect PSMA-positive tumors using PET scans in a cohort of prostate cancer (PCa) patients. METHODS: The [18F]AlF-P16-093 was automatically synthesized with a GE TRACERlab. A total of 23 patients with histopathologically proven PCa were prospectively enrolled. Dosimetry and biodistribution study investigations were carried out on a subset of six (6) PCa patients, involving multiple time-point scanning. The mean absorbed doses were estimated with PMOD and OLINDA software. RESULTS: [18F]AlF-P16-093 was successfully synthesized, and radiochemical purity was > 95%, and average labeling yield was 36.5 ± 8.3% (decay correction, n = 12). The highest tracer uptake was observed in the kidneys, spleen, and liver, contributing to an effective dose of 16.8 ± 1.3 µSv/MBq, which was ~ 30% lower than that of [68Ga]Ga-P16-093. All subjects tolerated the PET examination well, and no reportable side-effects were observed. The PSMA-positive tumors displayed rapid uptake, and they were all detectable within 10 min, and no additional lesions were observed in the following multi-time points scanning. Each patient had at least one detectable tumor lesion, and a total of 356 tumor lesions were observed, including intraprostatic, lymph node metastases, bone metastases, and other soft tissue metastases. CONCLUSIONS: We report herein a streamlined method for high yield synthesis of [18F]AlF-P16-093. Preliminary study in PCa patients has demonstrated its safety and acceptable radiation dosimetry. The initial diagnostic study indicated that [18F]AlF-P16-093 PET/CT is efficacious and potentially useful for a widespread application in the diagnosis of PCa patients.

A deep learning approach for electric motor fault diagnosis based on modified InceptionV3.

Electric motors are essential equipment widely employed in various sectors. However, factors such as prolonged operation, environmental conditions, and inadequate maintenance make electric motors prone to various failures. In this study, we propose a thermography-based motor fault detection method based on InceptionV3 model. To enhance the detection accuracy, we apply Contrast Limited Adaptive Histogram Equalization (CLAHE) to the input images. Furthermore, we improved the performance of the InceptionV3 by integrating a Squeeze-and-Excitation (SE) channel attention mechanism. The proposed model was tested using a dataset containing 369 thermal images of an electric motor with 11 types of faults. Image augmentation was employed to increase the data size and the evaluation was conducted using fivefold cross validation. Experimental results indicate that the proposed model can achieve accuracy, precision, recall, and F1 score of 98.82%, 98.93%, 98.82%, and 98.87%, respectively. Additionally, by freezing the fully connected layers of the InceptionV3 model for feature extraction and training a Support Vector Machines (SVM) to perform classification, it is able to achieve 100% detection rate across all four evaluation metrics. This research contributes to the field of industrial motor fault diagnosis. By incorporating deep learning techniques based on InceptionV3 and SE channel attention mechanism with a traditional classifier, the proposed method can accurately classify different motor faults.

Study of the utilization of main crop straw resources in Southern China and its potential as a replacement for chemical fertilizers.

Although straw returning to the field (SRTTF) is conducive to promoting sustainable agricultural production and protecting the environment, straw resources are still wasted due to the lack of suitable straw-returning technology in southern China. Based on the statistical yearbook and a large number of studies, different methods were used to calculate the total straw resources and SRTTF potential, and differences in these methods were compared. The results indicate that the total amount of straw resources in southern China in 2021 was 3.35×108 t. The nutrient content of K2O in the straw accounted for the highest proportion of total nutrient resources (63.66%), followed by N (26.88%) and P2O5 (9.46%). In theory, total SRTTF could replace almost all K2O and part of N and P2O5, indicating that the nutrient substitution potential of SRTTF was high. It is suggested that the SRTTF method be adopted in the middle and lower reaches of the Yangtze River, which mainly uses direct returning (DR) supplemented by indirect returning (IDR). In southeast China, straw returning is carried out by the combination of IDR and IR. In southwest China, straw returning is mainly carried out by IR and supplemented by MDR. This study will provide theoretical support for the government to formulate straw-returning policy.