Detection of detached fetal nucleated red blood cells (fNRBCs) in the maternal peripheral blood may serve as a prospective testing method competing with the cell-free DNA, in non-invasive prenatal testing (NIPT).Methods: Herein, we introduce a facile and effective lab-on-a-chip method of fNRBCs detection using a capture-releasing material that is composed of biotin-doped polypyrrole nanoparticles. To enhance local topographic interactions between the nano-components and fNRBC, a specific antibody, CD147, coated on the nanostructured substrate led to the isolation of fNRBCs from maternal peripheral blood. Subsequently, an electrical system was employed to release the captured cells using 0.8 V for 15 s. The diagnostic application of fNRBCs for fetal chromosomal disorders (Trisomy 13/21/18/X syndrome, microdeletion syndrome) was demonstrated.Results: Cells captured by nanostructured microchips were identified as fNRBCs. Twelve cases of chromosomal aneuploidies and one case of 18q21 microdeletion syndrome were diagnosed using the fNRBCs released from the microchips.Conclusion: Our method offers effective and accurate analysis of fNRBCs for comprehensive NIPT to monitor fetal cell development.

Background: To compare the diagnostic performance of radiomics models with that of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) perfusion parameters for the preoperative prediction of extramural venous invasion (EMVI) in rectal cancer patients and to develop a preoperative nomogram for predicting the EMVI status.Methods: In total, 106 rectal cancer patients were enrolled in our study. All patients under went preoperative rectal high-resolution MRI and DCE-MRI. We built five models based on the perfusion parameters of DCE-MRI (quantitative model), the radiomics of T 2 -weighted (T 2 W) CUBE imaging (R 1 model), DCE-MRI (R 2 model), clinical features (clinical model), and clinical-radiomics features. The predictive efficacy of the radiomics signature was assessed and internally verified. The area under the receiver operating curve (AUC) was used to compare the diagnostic performance of different radiomics models and DCE-MRI quantitative parameters. The radiomics score and clinical-pathologic risk factors were incorporated into an easy-to-use nomogram.Results: The quantitative parameters K trans and Ve were significantly higher in the EMVI-positive group than in the EMVI-negative group (both P =0.02). K trans combined with Ve showed a fair degree of accuracy (AUC 0.680 in the training cohort and AUC 0.715 in the validation cohort) compared with K trans or Ve alone. The AUCs of the R 1 and R 2 models were 0.826, 0.715 and 0.872, 0.812 in the training and validation cohorts, respectively. In addition, the R 2 -C model yielded an AUC of 0.904 in the training cohort and 0.812 in the validation cohort. The nomogram was presented based on the clinical-radiomics model. The calibration curves showed good agreement.Yu et al. Radiomics to Predict EMVI Conclusion:The radiomics nomogram that incorporates the radiomics score, histopathological grade and T stage demonstrated better diagnostic accuracy than the DCE-MRI quantitative parameters and may have significant clinical implications for the preoperative individualized prediction of EMVI in rectal cancer patients.

Objective: To determine whether noncontrast computed tomography (NCCT) models based on multivariable, radiomics features, and machine learning (ML) algorithms could further improve the discrimination of early hematoma expansion (HE) in patients with spontaneous intracerebral hemorrhage (sICH). Materials and Methods: We retrospectively reviewed 261 patients with sICH who underwent initial NCCT within 6 hours of ictus and follow-up CT within 24 hours after initial NCCT, between April 2011 and March 2019. The clinical characteristics, imaging signs and radiomics features extracted from the initial NCCT images were used to construct models to discriminate early HE. A clinical-radiologic model was constructed using a multivariate logistic regression (LR) analysis. Radiomics models, a radiomics-radiologic model, and a combined model were constructed in the training cohort (n = 182) and independently verified in the validation cohort (n = 79). Receiver operating characteristic analysis and the area under the curve (AUC) were used to evaluate the discriminative power. Results: The AUC of the clinical-radiologic model for discriminating early HE was 0.766. The AUCs of the radiomics model for discriminating early HE built using the LR algorithm in the training and validation cohorts were 0.926 and 0.850, respectively. The AUCs of the radiomics-radiologic model in the training and validation cohorts were 0.946 and 0.867, respectively. The AUCs of the combined model in the training and validation cohorts were 0.960 and 0.867, respectively. Conclusion: NCCT models based on multivariable, radiomics features and ML algorithm could improve the discrimination of early HE. The combined model was the best recommended model to identify sICH patients at risk of early HE.

BackgroundRobertsonian translocations occur in approximately one in every 1000 newborns. Although most Robertsonian translocation carriers are healthy and have a normal lifespan, they are at increased risk of spontaneous abortions and risk of producing unbalanced gametes and, therefore unbalanced offspring. Here we reported a previously undescribed Robertsonian translocation.Case PresentationWe identified three Robertsonian translocation carriers in this family. Two were heterozygous translocation carriers of 45,XX or XY,der(14;15)(q10;q10) and their son was a homozygous translocation carrier of a 44,XY,der(14;15)(q10;q10), der(14;15)(q10;q10) karyotype. Chromosomal analysis of sperm showed 99.7 % of sperm from the homozygous translocation carrier were normal/balanced while only 79.9 % of sperm from the heterozygous translocation carrier were normal/balanced. There was a significantly higher frequency of aneuploidy for sex chromosome in the heterozygous translocation carrier.ConclusionsThe reproductive fitness of Robertsonian translocation carriers is reduced. Robertsonian translocation homozygosity can be a potential speciation in humans with 44 chromosomes.

The frequency of the Robertonian (ROB) translocation in newborn babies is approximately one in 1000. Robertsonian translocation is an unusual type of chromosome rearrangement caused by two particular chromosomes joining together. The aim of the study was to analyze the segregation of the ROB translocations in 13 male carriers, and to verify a possible inter-chromosomal effect (ICE) of the ROB translocation on chromosomes 18, X, and Y. Thirteen male patients were included in the study. Multicolor fluorescent in situ hybridization (FISH) was used to analyze chromosomes 13, 14, 15, 21, 22, 18, X and Y in sperm. Among the heterozygous ROB translocation carriers, the frequency of normal/balanced spermatozoa resulting from alternate segregation varied between 70.4 and 85.2%. The frequency of unbalanced spermatozoa resulting from adjacent segregation varied between 14.8 and 29.6%. Increased frequencies of aneuploidy for a sex chromosome were found in 10 ROB translocation carriers (P2-P8, P10-P12). Increased frequencies of aneuploidy for chromosome 18 were found in10 ROB translocation carriers (P3-P9, P11-P13). In addition, increased frequencies of diploid were found in 11 ROB translocation carriers (P2-P9, P11-P13). Among the homozygous ROB translocation carriers, the rate of balanced spermatozoa was 99.7% and the frequency of unbalanced spermatozoa was 0.3%. However, the frequencies of aneuploidy for a sex chromosome and chromosome 18 were normal. Despite the high number of normal/balanced frequencies, there remained many unbalanced spermatozoa resulting from alternate segregation. The ROB translocation carriers may be at an increased risk for ICE. Robertsonian translocation homozygosity could be seen as a potential speciation in humans with 44 chromosomes.

Object detection in aerial images has received extensive attention in recent years. The current mainstream anchor-based methods directly divide the training samples into positives and negatives according to the intersection-over-unit (IoU) of the preset anchors. This label assignment strategy assigns densely arranged samples for training, which leads to a suboptimal learning process and cause the model to suffer serious duplicate detections and missed detections. In this paper, we propose a sparse label assignment strategy (SLA) to select high-quality sparse anchors based on the posterior IoU of detections. In this way, the inconsistency between classification and regression is alleviated, and better performance can be achieved through balanced training. Next, to accurately detect small and densely arranged objects, we use a position-sensitive feature pyramid network (PS-FPN) with a coordinate attention module to extract position-sensitive features for accurate localization. Finally, the distance rotated IoU loss is proposed to eliminate the inconsistency between the training loss and the evaluation metric for better bounding box regression. Extensive experiments on the DOTA, HRSC2016, and UCAS-AOD datasets demonstrate the superiority of the proposed approach.

Anecdotal reports of fertility in female mules (jack donkey × mare) and hinnies (stallion × jenny donkey) have appeared in the literature over the years, but scientists have generally regarded them with scepticism. The fact that some of these hybrids can come into estrous and ovulate makes fertility conceivable, given that opportunity for mating arises. In China, where mules are bred extensively for work on the farms, a fertile female mule and a fertile female hinny have now been verified by chromosomal investigation. Each had mated with a donkey and produced a filly foal. The foals show unique hybrid karyotypes different from the mule’s or hinny’s and different from each other’s. The studies make it clear that mule and hinny fertility, at least for the female hybrid, is a real possibility.

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