Search

Purpose: Iodine 123 labeled meta-iodobenzylguanidine ([123I]MIBG) scan with SPECT/CT imaging is one of the most commonly used imaging modalities in the evaluation of neuroblastoma. [18F]-meta-fluorobenzylguanidine ([18F]MFBG) is a novel positron emission tomography (PET) tracer which was reported to have a similar biodistribution to [123I]MIBG. However, the experience of using [18F]MFBG PET/CT in the evaluation of patients with neuroblastoma is limited. This preliminary investigation aims to assess the efficacy of [18F]MFBG PET/CT in the evaluation of neuroblastomas in comparison to [123I]MIBG scans with SPECT/CT. Materials and methods: In this prospective, single-center study, 40 participants (mean age 6.0 ± 3.7 years) with history of neuroblastoma were enrolled. All children underwent both [123I]MIBG SPECT/CT and [18F]MFBG PET/CT studies. The number of lesions and the Curie scores revealed by each imaging method were recorded. Results: Six patients had negative findings on both [123I]MIBG and [18F]MFBG studies. Four of the 34 patients (11.8%) were negative on [123I]MIBG but positive on [18F]MFBG, while 30 patients were positive on both [123I]MIBG and [18F]MFBG studies. In these 34 patients, [18F]MFBG PET/CT identified 784 lesions while [123I]MIBG SPECT/CT detected 532 lesions (p < 0.001). The Curie scores obtained from [18F]MFBG PET/CT (11.32 ± 8.18, range 1-27) were statistically higher (p < 0.001) than those from [123I]MIBG SPECT/CT (7.74 ± 7.52, range 0-26). 30 of 34 patients (88.2%) with active disease on imaging had higher Curie scores based on the [18F]MFBG study than on the [123I]MIBG imaging. Conclusion: [18F]MFBG PET/CT shows higher lesion detection rate than [123I]MIBG SPECT/CT in the evaluation of pediatric patients with neuroblastoma. Clinical trial registration: Clinicaltrials.gov: NCT05069220 (Registered: 25 September 2021, retrospectively registered); Institute Review Board of Peking Union Medical College Hospital: ZS-2514 [ABSTRACT FROM AUTHOR]

Water is the source of life, and in recent years, with the progress in technology, water quality data have shown explosive growth; how to use the massive amounts of data for water quality prediction services has become a new opportunity and challenge. In this paper, we use the surface water quality data of an area in Beijing collected and compiled by Zhongguancun International Medical Laboratory Certification Co., Ltd. (Beijing, China). On this basis, we decompose the original water quality indicator data series into two series in terms of trend and fluctuation; for the characteristics of the decomposed series data, we use the traditional time series prediction method to model the trend term, introduce the deep learning method to interpret the fluctuation term, and fuse the final prediction results. Compared with other models, our proposed integrated Wavelet decomposition, Autoregressive Integrated Moving Average (ARIMA) and Gated Recurrent Unit (GRU) model, which is abbreviated as the W-ARIMA-GRU model, has better prediction accuracy, stability, and robustness for three conventional water quality indicators. At the same time, this paper uses the ensemble learning model LightGBM for the prediction of water quality evaluation level, and the accuracy and F1-score reached 97.5% and 97.8%, respectively, showing very strong performance. This paper establishes a set of effective water quality prediction frameworks that can be used for timely water quality prediction and to provide a theoretical model and scientific and reasonable analysis reference for the relevant departments for advanced control. [ABSTRACT FROM AUTHOR]

Taking Beijing-Tianjin-Hebei as an example, it analyzes the comprehensive competitiveness of Beijing, Tianjin, and Hebei. It selects four dimensions: economic dimension, social dimension, environmental dimension, and technological dimension. From a new perspective, it explores the application of niche theory in regional synergy. Based on the analysis of the ecological niche, the coordination degree model of the composite system is further used to calculate the status quo of the coordinated development of the Beijing-Tianjin-Hebei region from 2013 to 2019. The results show that Beijing has the highest ecological niche, followed by Tianjin, and Hebei is the weakest. In 2019, the Beijing-Tianjin-Hebei region is at a good level of coordination, with the social subsystem having the highest order and the technological subsystem having the lowest order. Based on this, it is proposed that the Beijing-Tianjin-Hebei regions should be scientifically positioned, the overall need to be aligned with international trends, and the internal planning should be integrated to further enhance the level of cooperation in the Beijing-Tianjin-Hebei region. [ABSTRACT FROM AUTHOR]

Krukenberg tumours are not uncommon, but pregnancy-complicating Krukenberg tumours are rare. To identify management strategies of pregnancies with Krukenberg tumours, the medical records of patients treated at Peking Union Medical College Hospital over the past 20 years were collected and analysed. Four patients were enrolled. The primary tumour sites were the stomach and colorectal region. Three patients presented with obvious and severe gastrointestinal symptoms at 11-18 weeks of gestation, and their symptoms gradually developed into physiological signs associated with malignancy. Three patients underwent termination of pregnancy via induced delivery and gestational hysterectomy. One patient underwent caesarean section at 31 weeks of gestation. Two patients underwent palliative surgery due to extensive lesions. The other two patients with metastatic lesions confined to the ovaries and liver, underwent satisfactory cytoreductive surgery and anti-tumour treatments postoperatively. Pregnant women who exhibit new gastrointestinal symptoms or aggravation of previous gastrointestinal symptoms after the end of the first trimester should be carefully examined for digestive system diseases. If ovarian metastasis is highly suspected, the pregnancy should be terminated as early as possible. [ABSTRACT FROM AUTHOR]