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BackgroundPer- and polyfluoroalkyl substances (PFAS) are a class of persistent organic pollutants that possess potential toxicity to the human body. The production and utilization of diverse emerging PFAS have resulted in widespread human exposure. Therefore, it is imperative to establish a quantitative methodology encompassing a wide range of PFAS for a comprehensive assessment of human exposure to these compounds. ObjectiveTo establish a high-throughput quantitative method for the simultaneous determination of 53 PFAS in human serum based on ultra-high-performance liquid chromatography-Q Exactive high resolution mass spectrometry (UPLC-Q Exactive HRMS). MethodsThe extraction recoveries of hydrophilic-lipophilic balance (HLB) column, weak anionexchange (WAX) column, and 96-well WAX μElution plate were compared to select the SPE column with the highest recovery. The retention time and peak shape of the target compounds were compared between ACQUITY UPLC BEH C18 column and Accucore aQ column, and the more cost-effective column was chosen. The effects of adding different levels of ammonium formate (0, 2, 5 and 10 mmol·L−1) in mobile phase on peak shape and target response were compared to determine the optimal buffer salt concentration. The optimal spray voltage was obtained by comparing −2 kV and −4 kV. The proposed method was validated from the aspects of selectivity, standard curve, limits of detection, precision, accuracy, and matrix effect. The method was applied to 142 umbilical serum samples. ResultsThe best recovery rate (64%-118%) was achieved by using 96-well WAX μElution plate. The optimal separation and peak shape were obtained by utilizing Accucore aQ column with H2O-methanol (containing 5 mmol·L−1 ammonium formate) as the mobile phase. Less in-source collision and better target response were observed when the spray voltage was set to −2 kV. All target analytes had a good linearity, with R2 > 0.99. The limits of detection ranged from 0.01 to 0.50 μg·L−1, and the recovery ranged from 69% to 127% with the precision less than 26%. A total of 31 PFAS were detected in the 142 actual samples, among which 14 PFAS had a detection frequency over 50%. Perfluorooctanoic acid showed the highest median concentration of 4.16 μg·L−1, followed by 6:2 chlorinated polyfluorinated ether sulfonate and perfluorooctane sulfonates (3.50 μg·L−1 and 1.59 μg·L−1, respectively). ConclusionIn this study, we establish a UPLC-Q Excative HRMS method for simutanious determination of 53 PFAS concentrations in serum. This method has the advantages of wide coverage of PFAS, good selectivity, and easy operation, and is suitable for biological detection with a large sample size.

Abstract Histiocytic sarcoma is an aggressive haematopoietic malignancy accounting for less than 1% of haematolymphoid neoplasms with a diagnosis based on morphology and immunophenotype of tissue biopsies with a very poor prognosis. Here, we report a 45‐year‐old man who was diagnosed with primary pulmonary histiocytic sarcoma with systemic metastases, with partial remission (PR) treated with cyclophosphamide, doxorubicin, vincristine and prednisone (CHOP) chemotherapy, but it relapsed soon after therapy above. Tests demonstrated that TMB was 21 Muts/Mb PD‐L1 expression was 90% positive, and the disease has been well‐controlled over 3 years using immune checkpoint inhibitors (nivolumab and pembrolizumab). Bioinformatic pan‐cancer analysis verified that there was the highest genetic alteration frequency of PD‐L1 in which amplification accounted for the majority of sarcoma tumour samples. Following that, we found that the genetic alteration of PD‐L1 was associated with poor prognosis in sarcoma patients in terms of overall survival (OS) (p = 1.51 × 10−4), progress‐free survival (PFS) (p = 4.90 × 10−2) and disease‐specific survival (DSS) (p = 4.90 × 10−2). To our knowledge, this may be the first reported case with high PD‐L1 expression in primary pulmonary histiocytic sarcoma who may benefit from immunotherapy such as nivolumab and pembrolizumab significantly and safely.

Semantic segmentation for extracting buildings and roads from uncrewed aerial vehicle (UAV) remote sensing images by deep learning becomes a more efficient and convenient method than traditional manual segmentation in surveying and mapping fields. In order to make the model lightweight and improve the model accuracy, a lightweight network using object attention (LOANet) for buildings and roads from UAV aerial remote sensing images is proposed. The proposed network adopts an encoder-decoder architecture in which a lightweight densely connected network (LDCNet) is developed as the encoder. In the decoder part, the dual multi-scale context modules which consist of the atrous spatial pyramid pooling module (ASPP) and the object attention module (OAM) are designed to capture more context information from feature maps of UAV remote sensing images. Between ASPP and OAM, a feature pyramid network (FPN) module is used to fuse multi-scale features extracted from ASPP. A private dataset of remote sensing images taken by UAV which contains 2431 training sets, 945 validation sets, and 475 test sets is constructed. The proposed basic model performs well on this dataset, with only 1.4M parameters and 5.48G floating point operations (FLOPs), achieving excellent mean Intersection-over-Union (mIoU). Further experiments on the publicly available LoveDA and CITY-OSM datasets have been conducted to further validate the effectiveness of the proposed basic and large model, and outstanding mIoU results have been achieved. All codes are available on https://github.com/GtLinyer/LOANet.

Background: Hypercalcemia is a relatively common clinical problem. However, the differential diagnosis between hypercalcemia combined with hyperparathyroidism and a malignant tumor is difficult. Methods: Appropriate laboratory tests, ultrasound and static imaging of the parathyroid, electronic gastroscopy, and histological examinations were used. Results: The patient was found to have primary hyperparathyroidism due to hypercalcemia, with a parathyroid adenoma visible on color Doppler ultrasound and PET. The hypercalcemia was corrected after surgical resection. As the symptoms of nausea and vomiting did not improve, further investigations were undertaken, and gastric cancer was found on gastroscopy. Conclusions: Both primary hyperparathyroidism and gastric tumors may present with symptoms of nausea and vomiting. Clinically, multiple disease possibilities should be considered to explain a particular symptom. [ABSTRACT FROM AUTHOR]

This study developed a new method for the analysis of 20 phenolic compounds in human urine. The urine samples were prepared by hydrochloric acid (HCl) hydrolysis, liquid–liquid extraction (LLE), and solid-phase extraction (SPE) cleanup. We found that HCl hydrolysis is of similar effectiveness to, and much cheaper than, the traditional enzymatic method. Vanillic acid was co-eluted with butyl paraben and interfered with the determination of butyl paraben in urine. K2CO3-treated-silica-gel SPE was designed to efficiently eliminate interference from the endogenous organic acids (especially vanillic acid) in urine. After derivatization, the samples were analyzed by large-volume-injection gas chromatography–tandem mass spectrometry (LVI-GC–MS–MS). Good linearity (R 2 ≥ 0.996) was established in the range 0.1–100 ng mL−1 for all analytes. Method detection limits (MDLs) were 0.7–9.8 pg mL−1. Intraday (n = 5) and interday (n = 5 days) validation was performed, with satisfactory accuracy (recovery: 70–126 % and 73–107 %, respectively) and precision (RSD ≤ 19 %) at two levels (low: 0.1 and 0.5 ng mL−1; high: 5 and 10 ng mL−1). The method was used in a population study and achieved more than 85 % detection for most analytes; mean analyte concentrations were in the range 0.01–185 ng mL−1. The method is suitable for the analysis of multiple phenolic metabolites in human urine. [ABSTRACT FROM AUTHOR]