The Method of Lipemia Clearance Should be Based on the Characteristics and the Method of Testing in the Emergency Laboratory.

BACKGROUND: This study aimed to compare the lipemia removal efficiency of highspeed centrifugation, lipid scavengers, and dilution for biochemical analytes. METHODS: We collected 30 cases of lipemic plasma in an emergency laboratory and divided them into 4 aliquots. Lipemia was removed by highspeed centrifugation, lipid scavenger, dilution, and ultracentrifugation, then analytes were measured by an AU5800 analyzer. Taking ultracentrifugation as reference, the efficiencies of the other three methods were evaluated based on the deviation. RESULTS: When highspeed centrifugation was used for lipemia removal, DBIL (18.62%), and Magnesium (6.09%) could not satisfy the criterion. When lipid scavengers were applied to remove lipemia, CRP (-86.70%), TP (-8.29%), CKMB (-44.85%), DBIL (37.96%), Glu (4.20%) and phosphate (14.32%) were not suggested as lipid scavengers. For dilution, nearly half of the analytes could satisfy the criterion, including AMY (2.41%), CRP (5.54%), ALT (2.85%), GGTL (-1.73%), ALP (-0.04%), Glu (-0.84%), LDH (0.06%), CK (0.68%), BUN (3.80%), CREA (-1.54%), UA (5.42%), and magnesium (0.43%). CONCLUSIONS: Neither of the methods for lipid removal could satisfy all emergency department tests for lipid removal. This finding suggests that removing lipemia in the clinical laboratory should be based on the characteristics and the method of testing.

Microscale Normal Compression Behaviors of Clay Aggregates: A Coarse-Grained Molecular Dynamics Study.

Given the limitations of micromechanical experiments and molecular dynamics simulations, the normal compression process of clay aggregates was simulated under different vertical pressures (P), numbers of particles, loading methods, and environments by a Gay-Berne potential model. On the basis of the variations of particle orientation and the distribution of stacks, the evolution of deformation and stresses was elucidated. The results showed that the effects of the pressure level and loading environment on the deformation were significant. In the range of 0.1-10 MPa, the changes in the void ratio were essentially the evolution of the distribution of stacks determined by attractive short-range van der Waals interactions. The deformation under constant pressure was larger than that under step loading. Because the interactions between clay particles were mainly controlled by mechanical force when in the range of 40-100 MPa, the void ratios under various loading conditions were consistent. It was also found that changes in three-dimensional stresses during compression were dependent on those of the distribution of stacks. In the vacuum environment, owing to the lateral movement of interlocked small stacks, the horizontal stress decreased. The lateral pressure coefficients (k) were greater in an atmospheric environment because the anisotropic particle orientation was relatively less obvious. In the range of 10-100 MPa, when the loading path became longer, k was similar in vacuum but became smaller in an atmosphere. If the initial loading pressure was increased, the number of large stacks sharply increased and the anisotropy was significant in a vacuum environment, which was less prone to lateral expansion. In contrast, more consistent particle arrangements were maintained in an atmosphere. This work will be conducive to explaining experimental observations of long-term ripening.

Endosome associated trafficking regulator 1 promotes tumor growth and invasion of glioblastoma multiforme via inhibiting TNF signaling pathway.

PURPOSE: Endosome associated trafficking regulator 1 (ENTR1) is a novel endosomal protein, which can affect multiple cellular biological behavior by remodeling plasma membrane structures. However, little is known regarding its function and underlying mechanisms in glioblastoma multiforme. METHODS: Expression profile and clinical signature were obtained from The Public Database of human tumor. Immunohistochemical staining and western blotting assays were used to measure ENTR1 expression level. Human primary GBM tumor cells and human GBM cell lines A172, U87 and U251 were used to clarify the precise role of ENTR1. CCK-8 assays, wound healing and transwell invasion assays were designed to investigate cell viability, invasion and migration of GBM cells, respectively. Underlying molecular mechanisms of ENTR1 were determined via RNA-seq analysis. Tumor formation assay was used to validate the influence of ENTR1 in vivo. RESULTS: Compared with normal brain tissues, ENTR1 was highly expressed in gliomas and correlated with malignant grades of gliomas and poor overall survival time. The proliferation and invasion of GBM cells could be weaken and the sensitivity to temozolomide (TMZ) chemotherapy increased after knocking down ENTR1. Overexpression of ENTR1 could reverse this effect. RNA-seq analysis showed that tumor necrosis factor (TNF) signaling pathway might be a putative regulatory target of ENTR1. Tumor formation assay validated that ENTR1 was a significant factor in tumor growth. CONCLUSION: Our results indicated that ENTR1 played an important role in cell proliferation, invasion and chemotherapeutic sensitivity of GBM, suggesting that ENTR1 might be a novel prognostic marker and significant therapeutic target for GBM.

Correlation of abdominal muscle composition and abdominal aortic calcification in maintenance dialysis patients based on quantitative CT / 实用放射学杂志

Objective To measure the abdominal muscle composition of maintenance dialysis patients using quantitative computed tomography(QCT)and to analyze its relationship with abdominal aortic calcification(AAC).Methods The abdominal CT data of 193 maintenance dialysis patients were analyzed retrospectively and their clinical data were collected.The abdominal muscle composi-tion,including muscle area and muscle fat area,was measured at the middle level of L3 vertebral by QCT.The abdominal aortic calcifica-tion scores(AACs)were calculated using the Agatston method.The groups were grouped according to the quartiles of AACs,and differences in muscle area,muscle fat area and their associated variables were compared between the four groups.The relationship between abdominal muscle composition and AAC was assessed using Spearman rank correlation analysis and partial correlation analysis.Results AACs were positively correlated with age,male,dialysis age,diabetes,hypertension,and abdominal muscle fat area(r=0.555,0.172,0.192,0.348,0.335,0.358,all P<0.05),while no significant correlation was found with abdominal muscle area.A partial correlation analysis controlling for age,sex,dialysis age,hypertension and diabetes showed that AACs were still positively correlated with abdominal muscle fat area(r=0.183,P=0.012).Conclusion Abdominal muscle fat area in maintenance dialysis patients is positively associ-ated with the degree of AAC,and high abdominal muscle fat area is a risk factor for AAC.Enhanced muscle exercise may prevent the risk of vascular calcification in dialysis patients.

A pyroptosis gene-based prognostic model for predicting survival in low-grade glioma.

Background: Pyroptosis, a lytic form of programmed cell death initiated by inflammasomes, has been reported to be closely associated with tumor proliferation, invasion and metastasis. However, the roles of pyroptosis genes (PGs) in low-grade glioma (LGG) remain unclear. Methods: We obtained information for 1,681 samples, including the mRNA expression profiles of LGGs and normal brain tissues and the relevant corresponding clinical information from two public datasets, TCGA and GTEx, and identified 45 differentially expressed pyroptosis genes (DEPGs). Among these DEPGs, nine hub pyroptosis genes (HPGs) were identified and used to construct a genetic risk scoring model. A total of 476 patients, selected as the training group, were divided into low-risk and high-risk groups according to the risk score. The area under the curve (AUC) values of the receiver operating characteristic (ROC) curves verified the accuracy of the model, and a nomogram combining the risk score and clinicopathological characteristics was used to predict the overall survival (OS) of LGG patients. In addition, a cohort from the Gene Expression Omnibus (GEO) database was selected as a validation group to verify the stability of the model. qRT-PCR was used to analyze the gene expression levels of nine HPGs in paracancerous and tumor tissues from 10 LGG patients. Results: Survival analysis showed that, compared with patients in the low-risk group, patients in the high-risk group had a poorer prognosis. A risk score model combining PG expression levels with clinical features was considered an independent risk factor. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses indicated that immune-related genes were enriched among the DEPGs and that immune activity was increased in the high-risk group. Conclusion: In summary, we successfully constructed a model to predict the prognosis of LGG patients, which will help to promote individualized treatment and provide potential new targets for immunotherapy.

Analysis of factors with low positive predictive value in the diagnosis of urinary tract infection by flow cytometry.

PURPOSE: Culture-negative urine specimens can be rapidly screened by urine flow cytometry (UFC), while low positive predictive value (PPV) limits the clinical application. We explored the factors associated with a low PPV. METHODS: A total of 5095 urine specimens were analyzed with UFC and culture. Diagnostic performance of leukocytes, bacteria, and BACT-info flags was evaluated by sensitivity, specificity, PPV, and negative predictive value (NPV). The association of contaminated culture and squamous epithelial cell count and BACT-info flag was performed by logistic regression analysis. RESULTS: The NPVs of parallel combination of bacteria and leucocytes were 98.9% in males and 97.9% in females, and PPVs of serial combination were 86.6% and 77.8% in men and women, respectively. The PPV of Gram-negative flag was higher than that of Gram-positive flag. The proportions of contamination in the urine culture results of false positive specimens were 86.9% in males and 98.5% in females at the cutoff points of the serial combination, and these parameters were 53.2% in males and 85.6% in females for the Gram-positive flag. There was a statistically significant association between contaminated cultures and squamous epithelial cells count in females, but not in males. Associations between contaminated cultures and Gram-positive flags or Gram-pos/-neg flags were statistically significant, but there was no association between contaminated cultures and Gram-negative flags. CONCLUSIONS: A serial combination of leukocytes and bacteria may maximize PPV in the diagnosis of bacterial urinary tract infection by urine flow cytometry, and contamination is the main reason for a low PPV.

Contrast-enhanced magnetic resonance image segmentation based on improved U-Net and Inception-ResNet in the diagnosis of spinal metastases.

Objective: The objective of this study was to investigate the use of contrast-enhanced magnetic resonance imaging (CE-MRI) combined with radiomics and deep learning technology for the identification of spinal metastases and primary malignant spinal bone tumor. Methods: The region growing algorithm was utilized to segment the lesions, and two parameters were defined based on the region of interest (ROI). Deep learning algorithms were employed: improved U-Net, which utilized CE-MRI parameter maps as input, and used 10 layers of CE images as input. Inception-ResNet model was used to extract relevant features for disease identification and construct a diagnosis classifier. Results: The diagnostic accuracy of radiomics was 0.74, while the average diagnostic accuracy of improved U-Net was 0.98, respectively. the PA of our model is as high as 98.001%. The findings indicate that CE-MRI based radiomics and deep learning have the potential to assist in the differential diagnosis of spinal metastases and primary malignant spinal bone tumor. Conclusion: CE-MRI combined with radiomics and deep learning technology can potentially assist in the differential diagnosis of spinal metastases and primary malignant spinal bone tumor, providing a promising approach for clinical diagnosis.

PCR combined with serologic testing improves the yield and efficiency of SARS-CoV-2 infection hunting: A study in 40,689 consecutive overseas arrivals.

Background: The global epidemiological situation of COVID-19 remains serious. The rapid hunting of SARS-CoV-2 infection is the key means for preventing transmission. Methods: A total of 40,689 consecutive overseas arrivals were screened for SARS-CoV-2 infection based on PCR and serologic testing. The yield and efficiency of different screening algorithms were evaluated. Result: Among the 40,689 consecutive overseas arrivals, 56 (0.14%) subjects were confirmed to have SARS-CoV-2 infection. The asymptomatic rate was 76.8%. When the algorithm based on PCR alone was used, the identification yield of a single round of PCR (PCR1) was only 39.3% (95% CI: 26.1-52.5%). It took at least four rounds of PCR to achieve a yield of 92.9% (95% CI: 85.9-99.8%). Fortunately, an algorithm based on a single round of PCR combined with a single round of serologic testing (PCR1+ Ab1) greatly improved the screening yield to 98.2% (95% CI: 94.6-100.0%) and required 42,299 PCR and 40,689 serologic tests that cost 6,052,855 yuan. By achieving a similar yield, the cost of PCR1+ Ab1 was 39.2% of that of four rounds of PCR. For hunting one case in PCR1+ Ab1, 769 PCR and 740 serologic tests were required, costing 110,052 yuan, which was 63.0% of that of the PCR1 algorithm. Conclusion: Comparing an algorithm based on PCR alone, PCR combined with a serologic testing algorithm greatly improved the yield and efficiency of the identification of SARS-CoV-2 infection.

The primary application of indocyanine green fluorescence imaging in surgical oncology.

Background: Indocyanine green (ICG) is a nontoxic, albumin-bound, liver-metabolized fluorescent iodide dye that has been widely utilized in clinical applications since the mid-1950s. However, after the 1970s, in-depth research on the fluorescence properties of ICG greatly expanded its application in the medical field. Methods: In our mini-review, we searched the relevant literature on common oncology surgeries from PubMed, including lung cancer, breast cancer, gastric cancer, colorectal cancer, liver cancer, and pituitary tumors, using keywords such as indocyanine green, fluorescence imaging technology, and near-infrared fluorescence imaging. In addition, the application of targeted ICG photothermal technology in tumor therapy is briefly mentioned. Results: In this mini-review, we analyzed studies on ICG fluorescence imaging in common surgical oncology and offered a thorough analysis of each form of cancer or tumor. Conclusion: ICG has demonstrated significant potential in the detection and treatment of tumors in current clinical practice, although many applications are still in the preliminary stages, and multicenter studies are still required to more precisely define its indications, effectiveness, and safety.

Heterogenization of Salen Metal Molecular Catalysts in Covalent Organic Frameworks for Photocatalytic Hydrogen Evolution.

Integrating a molecular catalyst with a light harvester into a photocatalyst is an effective strategy for solar light conversion. However, it is challenging to establish a crystallized framework with well-organized connections that favour charge separation and transfer. Herein, we report the heterogenization of a Salen metal complex molecular catalyst into a rigid covalent organic framework (COF) through covalent linkage with the light-harvesting unit of pyrene for photocatalytic hydrogen evolution. The chemically conjugated bonds between the two units contribute to fast photogenerated electron transfer and thereby promote the proton reduction reaction. The Salen cobalt-based COF showed the best hydrogen evolution activity (1378 µmol g-1 h-1 ), which is superior to the previously reported nonnoble metal based COF photocatalysts. This work provides a strategy to construct atom-efficient photocatalysts by the heterogenization of molecular catalysts into covalent organic frameworks.

Exploratory study of WHO/ISUP classification of renal clear cell carcinoma pre-scholarly prediction based on ultrasonographic radiomics / 中华超声影像学杂志

Objective:To predict the clinical value of World Health Organization/International Society of Urological Pathology (WHO/ISUP) grading of clear cell renal cell carcinoma (ccRCC) pre-scholarly based on ultrasound imaging group.Methods:Clinical and ultrasound imaging data of patients with surgically pathologically confirmed ccRCC at Tianjin Medical University Cancer Institue and Hospital from January 2021 to October 2022 were retrospectively collected and divided into a low grade group (grade Ⅰ and Ⅱ, 105 cases) and a high grade group (grade Ⅲ and Ⅳ, 70 cases) using WHO/ISUP pathological grading criteria. The clear image of the largest diameter of the tumor was selected and imported into ITK-SNAP software for manual segmentation of the image and extraction of ultrasonographic radiomics features. The patients were randomly divided into a training group and a test group in the ratio of 7∶3, with 122 cases in the training group and 53 cases in the test group. Stable radiomics features were obtained by dimensionality reduction. The support vector machines (SVM) algorithm was applied to predict the pathological grading of ccRCC. Finally, a clinical-ultrasound imaging model, an ultrasonographic radiomics model and a comprehensive model combining the two were constructed. The predictive effects of the three models were analyzed by the area under the ROC curve (AUC). The performance of each model was evaluated by applying the calibration curve. The net benefit of patients was obtained by applying the decision curve.Results:A total of 873 radiomics features were extracted, and 10 features were finally obtained for model construction after dimensionality reduction. Final test results showed that the AUC, sensitivity, specificity and accuracy of the clinical-ultrasound imaging model were 0.68, 0.47, 0.78, 0.66. The AUC, sensitivity, specificity and accuracy of the ultrasonographic radiomics model were 0.74, 0.53, 0.88, 0.74. The AUC, sensitivity, specificity and accuracy of the comprehensive model were 0.84, 0.63, 0.86, 0.77. The AUC of the comprehensive model being larger than that of the clinical-ultrasound imaging model ( Z=-3.224, P=0.001) and ultrasonographic radiomics model ( Z=-2.594, P=0.009). The calibration curves showed that the comprehensive model was more stable than the other two models. The decision curve showed a higher net clinical benefit for the comprehensive model than for the other two models within a threshold of 0.1-1.0. Conclusions:The preoperative prediction of ccRCC pathological grading by the radiomics model based on ultrasound images is effective. The comprehensive model constructed by combining relevant clinical and ultrasound parameters has better performance, which can help predict ccRCC pathological grading preoperatively to a certain extent. It is crucial to help physicians choose the best management plan in the era of personalized medicine.

Prediction model of NIH risk stratification for gastrointestinal stromal tumor based on ultrasonographic radiomics by oral contrast enhanced ultrasonography / 中华超声影像学杂志

Objective:To investigate the prediction of National Institute of Healthy (NIH) risk stratification of gastrointestinal stromal tumor(GIST) based on clinical ultrasound model, ultrasonographic radiomics model and combined model by oral contrast enhanced ultrasonography.Methods:The clinical and ultrasound imaging data of 204 gastric GIST patients attending Tianjin Medical University Cancer Institute and Hospital from June 2021 to June 2022 were retrospectively analyzed, among whom a total of 101 patients with high and moderate NIH risk stratification GIST confirmed by postoperative pathology were included in the high risk group, and a total of 103 patients with low and extremely low NIH risk stratification GIST were in the low risk group. The ultrasound images of the largest diameter of the GIST were manually segmented by ITK-SNAP software, and Pyradiomics (v3.0.1) module in Python 3.8.7 was applied to extract ultrasonographic radiomics features from the ROI segmented images. The patients were randomly divided into training and validation sets in the ratio of 7∶3. The XGBoost of Sklearn module was applied to construct the clinical ultrasound imaging model, ultrasonographic radiomics model, and combined model. Then the area under ROC curve (AUC), sensitivity, specificity, and accuracy were evaluated; the predictive ability of the three models was compared by Delong test. Calibration Curve was applied to evaluate the model performance, and the clinical Decision Curve Analysis was applied to determine the net benefit to patients.Results:A total of 578 ultrasonographic radiomics features were extracted from ROI, and 8 ultrasonographic radiomics features were finally retained for modeling after regression and dimensionality reduction. Finally, test results showed that AUC, sensitivity, specificity and accuracy of clinical ultrasound imaging model, ultrasonographic radiomics model and combined model were 0.75, 69.3%, 68.9%, 69.1%; 0.87, 79.2%, 81.6%, 80.4%; 0.91, 80.2%, 83.5%, 81.9%, respectively. Delong test showed that the difference of AUC between ultrasonographic radiomics model and clinical ultrasound imaging model was statistically significant ( Z=2.698, P<0.001), and the combined model was significantly better than clinical ultrasound imaging model ( Z=4.062, P<0.001) and ultrasonographic radiomics model ( Z=2.225, P=0.026). Calibration Curve showed the high performance of combined model, and Decision Curve Analysis showed the superior clinical usefulness of combined model. Conclusions:It is feasible to construct an ultrasonographic radiomics model for GIST NIH risk stratification based on oral contrast enhanced ultrasonography images, and the combined model has more advantageous diagnostic performance, which can identify high risk NIH GIST objectively and stably for clinical purposes.

Application of strain ultrasonic elastography based on Image Pro Plus software in the diagnosis of Breast Imaging Reporting and Data System category 4 nodules / 肿瘤研究与临床

Objective:To explore the diagnostic value of strain ultrasonic elastography (SUE) supported by Image Pro Plus (IPP) software in distinguishing benign and malignant Breast Imaging Reporting and Data System (BI-RADS) category 4 nodules.Methods:The clinical and ultrasound imaging data of 192 female patients with BI-RADS category 4 nodules diagnosed by breast ultrasound in Tianjin Medical University Cancer Institute and Hospital from January 2020 to January 2021 were retrospectively analyzed. One nodule was selected for each patient, and a total of 192 nodules were analyzed. The ultrasound images and SUE images of each nodule were acquired before surgery, followed by BI-RADS classification scoring and SUE scoring. The IPP software was applied to outline the region of interest of all nodules, and the software automatically counted the SUE area ratio (SUE-IPP-AR) of all nodules. Using pathological diagnosis as the gold standard, SUE-IPP scoring was performed based on the optimal cut-off value of SUE-IPP-AR for distinguishing benign and malignant nodules according to receiver operating characteristic (ROC) curve. The efficacy of BI-RADS classification, SUE score, SUE-IPP score, and SUE-IPP+BI-RADS combined score in the differentiation of benign and malignant breast nodules were analyzed by ROC curve. Kappa coefficient was used to assess inter-observer agreement for SUE and SUE-IPP-AR.Results:Of the 192 nodules, 58 were benign nodules and 134 were malignant nodules diagnosed by pathology. These nodules were classified by BI-RADS, with 46 nodules in BI-RADS category 4A, 57 nodules in BI-RADS category 4B and 89 nodules in BI-RADS category 4C. SUE images 1-6 level were 12, 14, 41, 51, 42, and 32 nodules, respectively. ROC curve analysis showed that the optimal cut-off value of SUE-IPP for determining benign and malignant BI-RADS category 4 breast nodules was 58% [area under the curve (AUC) = 0.729, sensitivity 73%, specificity 69%]. The AUC of SUE-IPP+BI-RADS combined score for determining benign and malignant nodules was the largest (0.871), which was higher than that of BI-RADS score (AUC = 0.829, Z = 2.51, P = 0.012), SUE-IPP score (AUC = 0.729, Z = 3.56, P < 0.001) and SUE score (AUC = 0.695, Z = 4.37, P < 0.001). The sensitivity of SUE-IPP+BI-RADS combined score ≥ 3 points for diagnosing malignant nodules was 86.6%, while the specificity was 82.8%. Therefore, SUE-IPP+ BI-RADS score had the best efficacy for determining benign and malignant nodules. There was good agreement between sonographer with more than 5 years of experience and those with less than 5 years of experience in applying SUE to diagnose breast malignant nodules (Kappa = 0.768, 95% CI 0.711-0.825), and very good diagnostic agreement in applying SUE-IPP (Kappa = 0.946, 95% CI 0.919-0.974). Conclusions:SUE-IPP can improve the diagnostic ability for BI-RADS category 4 breast malignant nodules and can be used as an adjunct to ultrasound diagnosis.

Value of predictive liver metastasis in pancreatic neuroendocrine neoplasms based on ultrasonographic radiomics / 中华超声影像学杂志

Objective:To explore the predictive value of ultrasound-based radiomics for liver metastasis in pancreatic neuroendocrine tumors (pNEN).Methods:A retrospective analysis was conducted on clinical, pathological, and ultrasound data of 269 pNEN patients confirmed by pathology at Tianjin Medical University Cancer Institute and Hospital from January 2012 to June 2022, including 94 patients with liver metastasis and 175 without liver metastasis. The regions of interest (ROI) were delineated on the maximum diameter section of the tumor using ITKSNAP software, and radiomics features were extracted using Pyradiomics. Radiomics features with an intra-group correlation coefficient greater than 0.90 were retained, and the optimal features were selected using the maximum relevance minimum redundancy (MRMR) algorithm. The dataset was randomly divided into a training set and a validation set in a ratio of 7∶3, and the random forest algorithm (Rfs) was used to predict pNEN liver metastasis. Three models were constructed, including the clinical ultrasound model, the radiomics model, and the comprehensive model that combined clinical ultrasound and radiomics features. The predictive performance of different models for pNEN liver metastasis was analyzed using the ROC curve, and the predictive performance of different models was compared using the Delong test.Results:A total of 874 features were extracted from the ROI, and 12 highly robust radiomics features were retained for model construction based on inter- and intra-observer correlation grading and feature selection. The area under curve(AUC), sensitivity, specificity, and accuracy of the radiomics model, the clinical ultrasound model, and the comprehensive model for predicting liver metastasis in pNEN patients were 0.800, 0.574, 0.789, 0.714; 0.780, 0.596, 0.874, 0.777; and 0.890, 0.694, 0.874, 0.810, respectively. The Delong test showed that the comprehensive model had the best predictive performance, with an AUC superior to that of radiomics model ( Z=3.845, P=0.000 12) and clinical ultrasound model ( Z=3.506, P=0.000 45). Conclusions:The radiomics model based on ultrasound has good performance in predicting liver metastasis in pNEN, and the comprehensive model that combines clinical ultrasound and radiomics features can further improve the predictive performance of the model.

Unspecific reactivity must be excluded in COVID-19 epidemiological analyses or virus tracing based on serologic testing: Analysis of 46,777 post-pandemic samples and 1,114 pre-pandemic samples.

Background: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent of coronavirus disease 2019 (COVID-19). Serologic testing is complementary to nucleic acid screening to identify SARS-CoV-2. This study aimed to evaluate unspecific reactivity in SARS-CoV-2 serologic tests. Materials and methods: Total anti-SARS-CoV-2 antibodies from 46,777 subjects who were screened for SARS-CoV-2 were retrospectively studied to evaluate the incidence and characteristics of the unspecific reactivity. A total of 1,114 pre-pandemic samples were also analysed to compare unspecific reactivity. Results: The incidence of unspecific reactivity in anti-SARS-CoV-2 total antibody testing was 0.361% in 46,777 post-pandemic samples, similar to the incidence of 0.359% (4/1,114) in 1,114 pre-pandemic samples (p = 0.990). Subjects ≥ 19 years old had a 2.753-fold [95% confidence interval (CI), 1.130-6.706] higher probability of unspecific reactivity than subjects < 19 years old (p = 0.026). There was no significant difference between the sexes. The unspecific reactivity was associated with 14 categories within the disease spectrum, with three tops being the skin and subcutaneous tissue diseases (0.93%), respiratory system diseases (0.78%) and neoplasms diseases (0.76%). The percentage of patients with a titer ≥ 13.87 cut-off index (COI) in the unspecific reactivity was 7.69%. Conclusion: Our results suggest a unspecific reactivity incidence rate of 0.361% involving 14 categories on the disease spectrum. Unspecific reactivity needs to be excluded when performing serologic antibody testing in COVID-19 epidemiological analyses or virus tracing.

Automated meniscus segmentation and tear detection of knee MRI with a 3D mask-RCNN.

BACKGROUND: The diagnostic results of magnetic resonance imaging (MRI) are essential references for arthroscopy as an invasive procedure. A deviation between medical imaging diagnosis and arthroscopy results may cause irreversible damage to patients and lead to excessive medical treatment. To improve the accurate diagnosis of meniscus injury, it is urgent to develop auxiliary diagnosis algorithms to improve the accuracy of radiological diagnosis. PURPOSE: This study aims to present a fully automatic 3D deep convolutional neural network (DCNN) for meniscus segmentation and detects arthroscopically proven meniscus tears. MATERIALS AND METHODS: Our institution retrospectively included 533 patients with 546 knees who underwent knee magnetic resonance imaging (MRI) and knee arthroscopy. Sagittal proton density-weighted (PDW) images in MRI of 382 knees were regarded as a training set to train our 3D-Mask RCNN. The remaining data from 164 knees were used to validate the trained network as a test set. The masks were hand-drawn by an experienced radiologist, and the reference standard is arthroscopic surgical reports. The performance statistics included Dice accuracy, sensitivity, specificity, FROC, receiver operating characteristic (ROC) curve analysis, and bootstrap test statistics. The segmentation performance was compared with a 3D-Unet, and the detection performance was compared with radiological evaluation by two experienced musculoskeletal radiologists without knowledge of the arthroscopic surgical diagnosis. RESULTS: Our model produced strong Dice coefficients for sagittal PDW of 0.924, 0.95 sensitivity with 0.823 FPs/knee. 3D-Unet produced a Dice coefficient for sagittal PDW of 0.891, 0.95 sensitivity with 1.355 FPs/knee. The difference in the areas under 3D-Mask-RCNN FROC and 3D-Unet FROC was statistically significant (p = 0.0011) by bootstrap test. Our model detection performance achieved an area under the curve (AUC) value, accuracy, and sensitivity of 0.907, 0.924, 0.941, and 0.785, respectively. Based on the radiological evaluations, the AUC value, accuracy, sensitivity, and specificity were 0.834, 0.835, 0.889, and 0.754, respectively. The difference in the areas between 3D-Mask-RCNN ROC and radiological evaluation ROC was statistically significant (p = 0.0009) by bootstrap test. 3D Mask RCNN significantly outperformed the 3D-Unet and radiological evaluation demonstrated by these results. CONCLUSIONS: 3D-Mask RCNN has demonstrated efficacy and precision for meniscus segmentation and tear detection in knee MRI, which can assist radiologists in improving the accuracy and efficiency of diagnosis. It can also provide effective diagnostic indicators for orthopedic surgeons before arthroscopic surgery and further promote precise treatment.

Endometrial squamous cell carcinoma originating from the cervix: A case report.

BACKGROUND: Cervical squamous cell carcinoma (SCC) is the most common type of cervical carcinoma and is generally derived from a precancerous stage called cervical high-grade squamous intraepithelial lesion (HSIL). Usually, the cancer metastasizes through lymphatic or hematogenous dissemination, but rarely spreads upward into the uterus. Here, we report a case of cervical HSIL extending into the endometrium and finally progressing to SCC in the uterine cavity. CASE SUMMARY: A 57-year-old postmenopausal woman visited our department and requested a routine cervical check-up. Four years ago, she had undergone a cervical loop electrosurgical excision procedure because of HSIL found during the gynecological examination, and she had not been checked again since. This time, a relapse of the cervical HSIL was diagnosed along with uterine pyometra and endometrial polyps. After 2 wk of antibiotic treatment, a laparoscopic hysterectomy was performed, and the final pathological examination revealed that the cervical HSIL had spread directly upward into the uterine cavity, gradually developing into cervical SCC in the endometrium. CONCLUSION: Cervical HSIL/SCC can directly spread upward into the uterus with the most common symptoms of pyometra and cervical stenosis. More attention should be given to the early detection and prevention of this disease.

The Stability of Intact Parathyroid Hormone (PTH) in Different Types of Blood Collection Tubes.

BACKGROUND: Over past decades, the instability of parathyroid hormone (PTH) causes great interference for the clinical laboratory. Contradictory results were reported in many reports about storage conditions and suitable blood collection tubes to ensure PTH stability in the pretreatment phase. METHODS: This study recruited 30 participants including 10 healthy persons, 10 hemodialysis, and 10 hyperparathyroidism patients. Five types of blood collection tubes (EDTA-K3 tube, coagulant tube, heparin anticoagulant tube, gel separating tube, and plain tube) were included to determine whether they were suitable as blood-collecting vessels. The time points and conditions for testing samples included less than 2 hours, 4 hours, and 8 hours at room temperature, and, in parallel, 24 hours, 48 hours, and 72 hours in refrigeration. Two different judgement criteria were used to compare the stability of PTH in different blood vessels. RESULTS: Purely statistical analysis showed that 4 types of blood collection tubes could not perform the same storage ability as EDTA-K3 tube at "T0" time point. Plain tube had the largest drop among all types of blood collection tubes. Compared by pairwise t-test, EDTA-K3 tube could maintain intact PTH for 8 hours (p = 0.998) at room temperature and 24 hours (p = 0.053) in refrigeration. When comparing the total change limit (TCL = 18.8%), at room temperature, EDTA-K3 tube (7.0%), heparin tube (12.7%), coagulant tube (16.2%), and plain tube (17.6%) could maintain intact PTH for 8 hours, and GST can preserve PTH for 4 hours (18.2%). In refrigeration, EDTA-K3 tube could maintain PTH for 72 hours (7.5%) and heparin tube could maintain 24 hours (18.4%). The other three blood collection tubes could not preserve PTH in refrigeration (GST = 22.1%, coagulant tube = 20.3%, plain tube = 20.8%). CONCLUSIONS: PTH seems more stable in the EDTA-K3 tube than any other blood collection tubes and is followed next by the heparin anticoagulant tube. Plain tube and GST have faster degradation than other tubes and are not suggested to preserve intact PTH.

The U-shape relationship between pulse pressure level on inpatient admission and long-term mortality in acute coronary syndrome patients undergoing percutaneous coronary intervention.

The association between pulse pressure and long-term mortality was investigated among acute coronary syndrome (ACS) patients who received percutaneous coronary intervention (PCI). The study population included 5055 ACS patients in the Department of Cardiology of Beijing Friendship Hospital who were enrolled from January 2013 to July 2019. The median duration of follow-up was 24 months. Multivariate Cox regression was used to analyze the relationships between PP on inpatient admission and mortalities. Non-linear associations were studied by restricted cubic splines. Considering the heart function, the analyses were performed in the whole cohort and the LVEF > = 0.5 cohort separately. Subgroup analyses were performed according to the different diagnosis (the myocardial infarction subgroup and the unstable angina pectoris subgroup). When PP was used as categorical variable, the high PP group (≥61 mm Hg) significantly increased the risk of death compared with the intermediate PP group (50-60 mm Hg) in the both cohorts. When PP was used as continuous variable, a U-shape relationship were found between PP and mortalities in the whole cohort (p (for nonlinearity) = .005 and .003, respectively), with reference PP level of 55 mm Hg. However, this U-shape relationship disappeared in the LVEF > 0.5 cohort (p (for nonlinearity) = .111 and .117, respectively). The similar results were obtained in MI subgroup. From this study, the U-shape relationships between PP level and all-cause and cardiac mortalities were found in ACS patients who underwent PCI. The U-shape relationships disappeared in the LVEF > 0.5 cohort. The reference PP level was 55 mm Hg.

RhoGEF Trio Regulates Radial Migration of Projection Neurons via Its Distinct Domains / 神经科学通报·英文版

The radial migration of cortical pyramidal neurons (PNs) during corticogenesis is necessary for establishing a multilayered cerebral cortex. Neuronal migration defects are considered a critical etiology of neurodevelopmental disorders, including autism spectrum disorders (ASDs), schizophrenia, epilepsy, and intellectual disability (ID). TRIO is a high-risk candidate gene for ASDs and ID. However, its role in embryonic radial migration and the etiology of ASDs and ID are not fully understood. In this study, we found that the in vivo conditional knockout or in utero knockout of Trio in excitatory precursors in the neocortex caused aberrant polarity and halted the migration of late-born PNs. Further investigation of the underlying mechanism revealed that the interaction of the Trio N-terminal SH3 domain with Myosin X mediated the adherence of migrating neurons to radial glial fibers through regulating the membrane location of neuronal cadherin (N-cadherin). Also, independent or synergistic overexpression of RAC1 and RHOA showed different phenotypic recoveries of the abnormal neuronal migration by affecting the morphological transition and/or the glial fiber-dependent locomotion. Taken together, our findings clarify a novel mechanism of Trio in regulating N-cadherin cell surface expression via the interaction of Myosin X with its N-terminal SH3 domain. These results suggest the vital roles of the guanine nucleotide exchange factor 1 (GEF1) and GEF2 domains in regulating radial migration by activating their Rho GTPase effectors in both distinct and cooperative manners, which might be associated with the abnormal phenotypes in neurodevelopmental disorders.