Sex differences in fetal brain functional network topology.

The fetal period is a critical stage in brain development, and understanding the characteristics of the fetal brain is crucial. Although some studies have explored aspects of fetal brain functional networks, few have specifically focused on sex differences in brain network characteristics. We adopted the graph theory method to calculate brain network functional connectivity and topology properties (including global and nodal properties), and further compared the differences in these parameters between male and female fetuses. We found that male fetuses showed an increased clustering coefficient and local efficiency than female fetuses, but no significant group differences concerning other graph parameters and the functional connectivity matrix. Our study suggests the existence of sex-related distinctions in the topological properties of the brain network at the fetal stage of development and demonstrates an increase in brain network separation in male fetuses compared with female fetuses.

A study on whether deep learning models based on CT images for bone density classification and prediction can be used for opportunistic osteoporosis screening.

This study utilized deep learning to classify osteoporosis and predict bone density using opportunistic CT scans and independently tested the models on data from different hospitals and equipment. Results showed high accuracy and strong correlation with QCT results, showing promise for expanding osteoporosis screening and reducing unnecessary radiation and costs. PURPOSE: To explore the feasibility of using deep learning to establish a model for osteoporosis classification and bone density value prediction based on opportunistic CT scans and to verify its generalization and diagnostic ability using an independent test set. METHODS: A total of 1219 cases of opportunistic CT scans were included in this study, with QCT results as the reference standard. The training set: test set: independent test set ratio was 703: 176: 340, and the independent test set data of 340 cases were from 3 different hospitals and 4 different CT scanners. The VB-Net structure automatic segmentation model was used to segment the trabecular bone, and DenseNet was used to establish a three-classification model and bone density value prediction regression model. The performance parameters of the models were calculated and evaluated. RESULTS: The ROC curves showed that the mean AUCs of the three-category classification model for categorizing cases into "normal," "osteopenia," and "osteoporosis" for the training set, test set, and independent test set were 0.999, 0.970, and 0.933, respectively. The F1 score, accuracy, precision, recall, precision, and specificity of the test set were 0.903, 0.909, 0.899, 0.908, and 0.956, respectively, and those of the independent test set were 0.798, 0.815, 0.792, 0.81, and 0.899, respectively. The MAEs of the bone density prediction regression model in the training set, test set, and independent test set were 3.15, 6.303, and 10.257, respectively, and the RMSEs were 4.127, 8.561, and 13.507, respectively. The R-squared values were 0.991, 0.962, and 0.878, respectively. The Pearson correlation coefficients were 0.996, 0.981, and 0.94, respectively, and the p values were all < 0.001. The predicted values and bone density values were highly positively correlated, and there was a significant linear relationship. CONCLUSION: Using deep learning neural networks to process opportunistic CT scan images of the body can accurately predict bone density values and perform bone density three-classification diagnosis, which can reduce the radiation risk, economic consumption, and time consumption brought by specialized bone density measurement, expand the scope of osteoporosis screening, and have broad application prospects.

Proteus appendicitidis sp. nov., isolated from the appendiceal pus of an appendicitis patient in Yongzhou, China.

A Gram-negative, facultatively anaerobic, short rod-shaped bacterium, designated as strain HZ0627T, was isolated from the appendiceal pus of a patient with appendicitis in Yongzhou, Hunan, China. This strain was subjected to comprehensive phenotypic, phylogenetic, and genomic analyses using polyphasic taxonomic methods. Phylogenetic analysis of the 16S rRNA gene sequence revealed that this strain belonged to the genus Proteus and the family Morganellaceae, whereas that based on the rpoB gene sequence and phylogenomic analysis demonstrated that this strain was distinctly separated from other type strains of Proteus species. Moreover, whole-genome-based analyses, including in silico DNA-DNA hybridization (isDDH) and average nucleotide identity (ANI), revealed that strain HZ0627T had much lower isDDH rates (24.5-55.6%) and ANI (82.04-93.90%) than those of the thresholds (i.e., 70% and 95%, respectively) for species delineation, when compared to the type strains of other Proteus species. The cellular fatty acid profile of strain HZ0627T was dominated by C16:0 (34.5%), cyclo C17:0 (25.8%), C14:0 (12.6%), C16:1 iso I/14:0 3-OH (7.7%), C18:1ω7c/18:1ω6c (6.5%), and C16:1ω7c/16:1ω6c (4.9%), which clearly differentiated it from the documented type strains of Proteus species. In addition, several specific physiological traits, including optimal growth temperature, tolerance to sodium chloride, and carbon source utilization, differed from those of other Proteus species. Therefore, we propose the name Proteus appendicitidis sp. nov. for strain HZ0627T (= CCTCC AB 2022380T = KCTC 92986T), which represents the type strain of this novel Proteus species.

Abnormal cerebral blood flow in children with developmental stuttering.

BACKGROUND: Stuttering affects approximately 5% of children; however, its neurological basis remains unclear. Identifying imaging biomarkers could aid in early detection. Accordingly, we investigated resting-state cerebral blood flow (CBF) in children with developmental stuttering. METHODS: Pulsed arterial spin labelling magnetic resonance imaging was utilised to quantify CBF in 35 children with developmental stuttering and 27 healthy controls. We compared normalised CBF between the two groups and evaluated the correlation between abnormal CBF and clinical indicators. RESULTS: Compared with healthy controls, the stuttering group exhibited decreased normalised CBF in the cerebellum lobule VI bilaterally, right cuneus, and left superior occipital gyrus and increased CBF in the right medial superior frontal gyrus, left rectus, and left dorsolateral superior frontal gyrus. Additionally, normalised CBF in the left cerebellum lobule VI and left superior occipital gyrus was positively correlated with stuttering severity. CONCLUSIONS: Children who stutter display decreased normalised CBF primarily in the cerebellum and occipital gyrus, with increased normalised CBF in the frontal gyrus. Additionally, the abnormal CBF in the left cerebellum lobule VI and left superior occipital gyrus was associated with more severe symptoms, suggesting that decreased CBF in these areas may serve as a novel neuroimaging clue for stuttering. IMPACT: Stuttering occurs in 5% of children and often extends into adulthood, which may negatively affect quality of life. Early detection and treatment are essential. We used pulsed arterial spin labelling magnetic resonance imaging to visualise the resting-state cerebral blood flow (CBF) in children who stutter and healthy children. Normalised CBF was decreased in stutterers in the cerebellum and occipital gyrus and increased in the frontal gyrus. Stuttering severity was linked to abnormal normalised CBF in the left cerebellum lobule VI and left superior occipital gyrus, suggesting that CBF may serve as a novel neuroimaging clue for stuttering.

Brain and the whole-body bone imaging appearances in Menkes disease: a case report and literature review.

BACKGROUND: Menkes disease (MD) is a rare, inherited, multisystemic copper metabolism disorder. Classical Menkes disease is characterized by low serum copper and ceruloplasmin concentrations, leading to multiple abnormalities in the whole-body, especially in connective tissue and central nervous system. However, serum copper and ceruloplasmin levels are not reliable diagnostic biomarkers due to the low concentrations in healthy newborns either. The featured imaging manifestations play an important role in diagnosing Menkes disease. To our knowledge, there are few reports on the systemic imaging manifestations of Menkes disease. CASE PRESENTATION: A 4-month-old male patient presented with recurrent seizures. He had cognitive, intellectual, growth, gross motor, precision movement, and language developmental lags. The patient's hemoglobin and serum ceruloplasmin level were low. On MRI, increased intracranial vascular tortuosity, cerebral and cerebellar atrophy, white matter changes, and basal ganglia abnormalities were observed. Plain radiograph revealed wormian bones, rib flaring, metaphyseal spurring, and periosteal reactions in the long bones of the limbs. A pathogenic variant in ATP7A gene was identified in the patient, so he was confirmed the diagnosis of Menkes disease. His symptoms did not improve despite symptomatic and supportive treatment during his hospitalization. Unfortunately, the infant died 3 months after leaving hospital. CONCLUSION: A comprehensive and intuitive understanding of the disease's imaging manifestations can help clinicians to identify the disease and avoid delays in care.

The differential value of radiomics based on traditional T1-weighted sequences in newborns with hyperbilirubinemia.

BACKGROUND: On the basis of visual-dependent reading method, radiological recognition and assessment of neonatal hyperbilirubinemia (NH) or acute bilirubin encephalopathy (ABE) on conventional magnetic resonance imaging (MRI) sequences are challenging. Prior studies had shown that radiomics was possible to characterize ABE-induced intensity and morphological changes on MRI sequences, and it has emerged as a desirable and promising future in quantitative and objective MRI data extraction. To investigate the utility of radiomics based on T1-weighted sequences for identifying neonatal ABE in patients with hyperbilirubinemia and differentiating between those with NH and the normal controls. METHODS: A total of 88 patients with NH were enrolled, including 50 patients with ABE and 38 ABE-negative individuals, and 70 age-matched normal neonates were included as controls. All participants were divided into training and validation cohorts in a 7:3 ratio. Radiomics features extracted from the basal ganglia of T1-weighted sequences on magnetic resonance imaging were evaluated and selected to set up the prediction model using the K-nearest neighbour-based bagging algorithm. A receiver operating characteristic curve was plotted to assess the differentiating performance of the radiomics-based model. RESULTS: Four of 744 radiomics features were selected for the diagnostic model of ABE. The radiomics model yielded an area under the curve (AUC) of 0.81 and 0.82 in the training and test cohorts, with accuracy, precision, sensitivity, and specificity of 0.82, 0.80, 0.91, and 0.69 and 0.78, 0.8, 0.8, and 0.75, respectively. Six radiomics features were selected in this model to distinguish those with NH from the normal controls. The AUC for the training cohort was 0.97, with an accuracy of 0.92, a precision of 0.92, a sensitivity of 0.93, and a specificity of 0.90. The performance of the radiomics model was confirmed by testing the test cohort, and the AUC, accuracy, precision, sensitivity, and specificity were 0.97, 0.92, 0.96, 0.89, and 0.95, respectively. CONCLUSIONS: The proposed radiomics model based on traditional TI-weighted sequences may be used effectively for identifying ABE and even differentiating patients with NH from the normal controls, which can provide microcosmic information beyond experience-dependent vision and potentially assist in clinical diagnosis and treatment.

Preliminary Study on Quantitative Assessment of the Fetal Brain Using MOLLI T1 Mapping Sequence.

BACKGROUND: Prenatal quantitative evaluation of myelin is important. However, few techniques are suitable for the quantitative evaluation of fetal myelination. PURPOSE: To optimize a modified Look-Locker inversion recovery (MOLLI) T1 mapping sequence for fetal brain development study. STUDY TYPE: Prospective observational preliminary cohort study. POPULATION: A total of 71 women with normal fetuses divided into mid-pregnancy (gestational age 24-28 weeks, N = 25) and late pregnancy (gestational age > 28 weeks, N = 46) groups. FIELD STRENGTH/SEQUENCE: A 3 T/MOLLI sequence. ASSESSMENT: T1 values were measured in pedunculus cerebri, basal ganglia, thalamus, posterior limb of the internal capsule, temporal white matter, occipital white matter, frontal white matter, and parietal white matter by two radiologists (11 and 16 years of experience, respectively). STATISTICAL TESTS: The Kruskal-Wallis test was used for reginal comparison. For each region of interest (ROI), differences in T1 values between the mid and late pregnancy groups were assessed by the Mann Whitney U test. Pearson correlation coefficients (r) were used to evaluate the correlations between T1 values and gestational age for each ROI. Intraobserver and interobserver agreement was determined by the intraclass correlation coefficient (ICC). A P value <0.05 was considered statistically significant. RESULTS: Interobserver and intraobserver agreements of T1 were good for all ROIs (all ICCs > 0.700). There were significant differences in T1 values between lobal white matter and deep regions, respectively. Significant T1 values differences were found between middle and late pregnancy groups in pedunculus cerebri, basal ganglion, thalamus, posterior limb of the internal capsule, temporal, and occipital white matter. The T1 values showed significantly negative correlations with gestational weeks in pedunculus cerebri (r = -0.80), basal ganglion (r = -0.60), thalamus (r = -0.68), and posterior limb of the internal capsule (r = -0.77). DATA CONCLUSION: The T1 values of fetal brain may be assessed using the MOLLI sequence and may reflect the myelination. EVIDENCE LEVEL: 3 TECHNICAL EFFICACY: Stage 2.

Hepatic Steatosis: CT-Based Prevalence in Adults in China and the United States and Associations With Age, Sex, and Body Mass Index.

BACKGROUND. Calibrated CT fat fraction (FFCT) measurements derived from un-enhanced abdominal CT reliably reflect liver fat content, allowing large-scale population-level investigations of steatosis prevalence and associations. OBJECTIVE. The purpose of this study was to compare the prevalence of hepatic steatosis, as assessed by calibrated CT measurements, between population-based Chinese and U.S. cohorts, and to investigate in these populations the relationship of steatosis with age, sex, and body mass index (BMI). METHODS. This retrospective study included 3176 adults (1985 women and 1191 men) from seven Chinese provinces and 8748 adults (4834 women and 3914 men) from a single U.S. medical center, all drawn from previous studies. All participants were at least 40 years old and had undergone unenhanced abdominal CT in previous studies. Liver fat content measurements on CT were cross-calibrated to MRI proton density fat fraction measurements using phantoms and expressed as adjusted FFCT measurements. Mild, moderate, and severe steatosis were defined as adjusted FFCT of 5.0-14.9%, 15.0-24.9%, and 25.0% or more, respectively. The two cohorts were compared. RESULTS. In the Chinese and U.S. cohorts, the median adjusted FFCT for women was 4.7% and 4.8%, respectively, and that for men was 5.8% and 6.2%, respectively. In the Chinese and U.S. cohorts, steatosis prevalence for women was 46.3% and 48.7%, respectively, whereas that for men was 58.9% and 61.9%, respectively. Severe steatosis prevalence was 0.9% and 1.8% for women and 0.2% and 2.6% for men in the Chinese and U.S. cohorts, respectively. Adjusted FFCT did not vary across age decades among women or men in the Chinese cohort, although it increased across age decades among women and men in the U.S. cohort. Adjusted FFCT and BMI exhibited weak correlation (r = 0.312-0.431). Among participants with normal BMI, 36.8% and 38.5% of those in the Chinese and U.S. cohorts, respectively, had mild steatosis, and 3.0% and 1.5% of those in the Chinese and U.S. cohorts, respectively, had moderate or severe steatosis. Among U.S. participants with a BMI of 40.0 or greater, 17.7% had normal liver content. CONCLUSION. Steatosis and severe steatosis had higher prevalence in the U.S. cohort than in the Chinese cohort in both women and men. BMI did not reliably predict steatosis. CLINICAL IMPACT. The findings provide new information on the dependence of hepatic steatosis on age, sex, and BMI.

Optimization of the image contrast for the developing fetal brain using 3D radial VIBE sequence in 3 T magnetic resonance imaging.

BACKGROUND: Faster and motion robust magnetic resonance imaging (MRI) sequences are desirable in fetal brain MRI. T1-weighted images are essential for evaluating fetal brain development. We optimized the radial volumetric interpolated breath-hold examination (VIBE) sequence for qualitative T1-weighted images of the fetal brain with improved image contrast and reduced motion sensitivity. MATERIALS AND METHODS: This was an institutional review board-approved prospective study. Thirty-five pregnant subjects underwent fetal brain scan at 3 Tesla MRI. T1-weighted images were acquired using a 3D radial VIBE sequence with flip angles of 6º, 9º, 12º, and 15º. T1-weighted images of Cartesian VIBE sequence were acquired in three of the subjects. Qualitative assessments including image quality and motion artifact severity were evaluated. The image contrast ratio between gray and white matter were measured. Interobserver reliability and intraobserver repeatability were assessed using intraclass correlation coefficient (ICC). RESULTS: Interobserver reliability and intraobserver repeatability universally revealed almost perfect agreement (ICC > 0.800). Significant differences in image quality were detected in basal ganglia (P = 0.023), central sulcus (P = 0.028), myelination (P = 0.007) and gray matter (P = 0.023) among radial VIBE with flip angles 6º, 9º, 12º, 15º. Image quality at the 9º flip angle in radial VIBE was generally better than flip angle of 15º. Radial VIBE sequence with 9º flip angle of gray matter was significantly different by gestational age (GA) before and after 28 weeks (P = 0.036). Quantified image contrast was significantly different among different flip angles, consistent with qualitative analysis of image quality. CONCLUSIONS: Three-dimensional radial VIBE with 9º flip angle provides optimal, stable T1-weighted images of the fetal brain. Fetal brain structure and development can be evaluated using high-quality images obtained using this angle. However, different scanners will achieve different TRs and so the FA should be re-optimized each time a new protocol is employed.

Sevoflurane inhibits the malignant phenotypes of glioma through regulating miR-146b-5p/NFIB axis.

PURPOSE: Sevoflurane is a common used inhaled anesthetic that was reported to regulate the progression of multiple cancers. Here, we aimed to investigate the function and regulatory mechanism underlying sevoflurane in glioma cells. METHODS: A172 and U251 cells were treated with different concentrations of sevoflurane. Colony formation, EdU satining and 3-(4,5-dimethyl-2-thiazolyl)-2,5-diphenyl-2-H-tetrazolium bromide (MTT), flow cytometry, and transwell assays were performed to evaluate cell proliferation, apoptosis, migration and invasion, respectively. Circ_VCAN, microRNA-146b-5p (miR-146b-5p) and nuclear factor I B (NFIB) expression levels were assessed by real-time quantitative PCR (RT-qPCR) or western blot. Bioinformatics analysis and dual-luciferase reporter assay were applied to evaluate the correlation between miR-146b-5p and circ_VCAN or NFIB. A xenograft glioma mice model was established to verify the effect of sevoflurane on tumor growth in vivo. RESULTS: Sevoflurane (Sev) inhibited proliferation, migration, invasion, and elevated apoptosis of A172 and U251 cells. Sevoflurane treatment inhibited the expression of circ_VCAN and NFIB, but elevated the expression of miR-146b-5p in glioma cells. Overexpression of circ_VCAN alleviated the inhibition effects of sevoflurane on the malignant phenotypes of glioma in vitro and in vivo. Besides, miR-146b-5p is a target of circ_VCAN and negatively regulated NFIB expression. Overexpression of miR-146b-5p partly reversed the effects of circ_VCAN in Sev-treated glioma cells. Furthermore, miR-146b-5p deletion enhanced glioma progression in sevoflurane treated glioma cells by targeting NFIB. Moreover, circ_VCAN could upregulate NFIB expression by sponging miR-146b-5p in Sev-treated glioma cells. CONCLUSION: Sevoflurane alleviated proliferation, migration and invasion, but enhanced apoptosis of glioma cells through regulating circ_VCAN/miR-146b-5p/NFIB axis.

MRI characteristics of the fetal tethered spinal cord: a comparative study.

Purpose: To compare fetuses and children with confirmed tethered cord syndrome to age-matched controls to provide a reference for prenatally identifying tethered spinal cord and to identify salient points on MRI for diagnosis.Materials and Methods: This retrospective study enrolled 13 fetuses and 20 children with tethered cord syndrome, and age-matched counterparts were included as controls. The MRI features including concomitant malformations, position of the conus medullaris, and thickened filum terminale of the two patient groups were evaluated and compared. Levels of the conus medullaris were discriminated between patients and an equivalent number of controls.Results: Various concomitant malformations manifested on the MRI of all patients, and there were differences between the two patient groups. Significant differences of the level of the conus medullaris were found between the fetal and child patients (U, 26.50; Z, -3.87; p < 0.001) and between the normal fetus and child controls (U, 23.50; Z, -4.13; p < 0.001). The position of the conus medullaris was visibly lower in the patient groups than in the control groups. No significant difference in the diameters of the filum terminale was found between the fetal and child patients (p = 0.67).Conclusions: The current study's results indicate that tethered spinal cord syndrome can be diagnosed in utero with MRI combined with several characteristics, particularly the position of the conus medullaris. Special attention should be paid to the gestational age of the fetus because normal changes in spinal cord position occur with gestational development.

A rare mutant of OFD1 gene responsible for Joubert syndrome with significant phenotype variation.

Joubert syndrome (JBTS), a rare genetic disorder resulted from primary cilium defects or basal-body dysfunction, is characterized by agenesis of cerebellar vermis and abnormal brain stem. Both genotypes and phenotypes of JBTS are highly heterogeneous. The identification of pathogenic gene variation is essential for making a definite diagnosis on JBTS. Here, we found that hypoplasia of cerebellar vermis occurred in three male members in a Chinese family. Then, we performed whole exome sequencing to identify a novel missense mutation c.599T > C (p. L200P) in the OFD1 gene which is the candidate gene of X-linked JBTS (JBST10). The following analysis showed that the variant was absent in the 1000 Genomes, ExAC and the 200 female controls; the position 200 Leucine residue was highly conserved across species; the missense variant was predicted to be deleterious using PolyPhen-2, PROVEAN, SIFT and Mutation Taster. The OFD1 expression was heavily lower in the proband and an induced male fetus compared with a healthy male with a wild-type OFD1 gene. The in vitro expression analysis of transiently transfecting c.599T or c.599C plasmids into HEK-293T cells confirmed that the missense mutation caused OFD1 reduction at the protein level. And further the mutated OFD1 decreased the level of Gli1 protein, a read-out of Sonic hedgehog (SHH) signaling essential for development of central neural system. A known pathogenic variant c.515T > C (p. L172P) showed the similar results. All of these observations suggested that the missense mutation causes the loss function of OFD1, resulting in SHH signaling impairs and brain development abnormality. In addition, the three patients have Dandy-Walker malformation, macrogyria and tetralogy of Fallot, respectively, the latter two of which are firstly found in JBTS10 patients. In conclusion, our findings expand the context of genotype and phenotype in the JBTS10 patients.

Short report: factors determining perceived stress among medical staff in radiology departments during the COVID-19 outbreak.

Medical staff in radiology departments faces a higher risk of infection and a heavier workload during the new coronavirus disease (COVID-19) outbreak. High perceived stress levels endanger physical and mental health and affect work efficiency and patient safety. Therefore, it is urgent to understand the perceived stress levels of medical staff and explore its risk factors. We recruited 600 medical staff from the radiology departments of 32 public hospitals in Sichuan Province, China, to evaluate perceived stress scores via a mobile app-based questionnaire. The results showed that the perceived stress level among medical staff in the radiology departments during the COVID-19 outbreak was high and a sense of tension was strongly present. A positive correlation was found between anxiety score and perceived stress. Multivariate analysis showed that risk factors for perceived stress were female, existing anxiety, and fears of being infected at work, an uncontrollable outbreak, and not being able to pay rent or mortgage. Conversely, good knowledge about COVID-19, being unmarried, and working in a higher-grade hospital were protective factors for perceived stress. Therefore, more attention should be given to medical staff in the radiology departments that present the risk factors outlined above. Timely risk assessment of psychological stress and effective intervention measures should be taken for these high-risk groups to keep their perceived stress within normal limits.

Factors Influencing Anxiety of Health Care Workers in the Radiology Department with High Exposure Risk to COVID-19.

BACKGROUND During the outbreak of COVID-19, health care workers in the radiology department frequently interact with suspected patients and face a higher risk of infection and sudden surges in workload. High anxiety levels seriously harm physical and mental health and affect work efficiency and patient safety. Therefore, it is critical to determine anxiety levels of health care workers and explore its risk factors. MATERIAL AND METHODS Self-Rating Anxiety Scale and Connor-Davidson Resilience Scale were used to evaluate the anxiety and resilience of 364 health care workers with high exposure risk from the radiology departments of 32 public hospitals in Sichuan Province, China. Multivariate linear regression was used to analyze factors related to anxiety. RESULTS The mean anxiety score was 44.28±8.93 and 23.4% of our study participants reported mild (n=63), moderate (n=19), or severe (n=3) anxiety. Multiple linear regression analysis showed that age, job position, availability of protective materials, signs of suspected symptoms, and susceptibility to emotions and behaviors of people around them were identified as risk factors for anxiety, whereas psychological resilience was identified as a protective factor. CONCLUSIONS Our study suggests that the anxiety level of health care workers in the radiology department with a high exposure risk to COVID-19 was high in the early stage of the outbreak, although the majority remained within normal limits. Timely assessment and effective intervention measures can improve the mental health of these at-risk populations.

Factors Associated with Resilience Among Medical Staff in Radiology Departments During The Outbreak of 2019 Novel Coronavirus Disease (COVID-19): A Cross-Sectional Study.

BACKGROUND A growing body of evidence suggests that in the face of life adversity, threats, or other major stressful events, resilience is more conducive to individual adaptation and growth. MATERIAL AND METHODS The Connor-Davidson Resilience Scale and the Chinese Perceived Stress Scale were used to evaluate the resilience and perceived stress of 600 medical staff members from the radiology departments in 32 public hospitals in Sichuan Province, China, respectively. Multiple linear regression was used to analyze factors related to resilience. RESULTS The total resilience score was 65.76±17.26, wherein the toughness dimension score was 33.61±9.52, the strength dimension score was 21.25±5.50, and the optimism dimension score was 10.91±3.15. There was a significant negative correlation between perceived stress and resilience (r=-0.635, P<0.001). According to multivariate analysis, the total perceived stress score (ß=-1.318, P<0.001), gender (ß=-4.738, P<0.001), knowledge of COVID-19 (ß=2.884, P=0.043), knowledge of COVID-19 protective measures (ß=3.260, P=0.042), and availability of adequate protective materials (ß=-1.268, P=0.039) were independent influencing factors for resilience. CONCLUSIONS The resilience level of the medical staff in the radiology departments during the outbreak of COVID-19 was generally low, particularly regarding toughness. More attention should be paid to resilience influence factors such as high perceived stress, female gender, lack of understanding of COVID-19 and protective measures, and lack of protective materials, and targeted interventions should be undertaken to improve the resilience level of the medical staff in the radiology departments during the outbreak of COVID-19.

Identification of suspicious invasive placentation based on clinical MRI data using textural features and automated machine learning.

OBJECTIVE: The aim of this study was to investigate whether intraplacental texture features from routine placental MRI can objectively and accurately predict invasive placentation. MATERIAL AND METHODS: This retrospective study includes 99 pregnant women with pathologically confirmed placental invasion and 56 pregnant women with simple placenta previa. All participants underwent magnetic resonance imaging after 24 gestational weeks. The placenta was segmented in sagittal images from both turbo spin echo (TSE) and balanced turbo field echo (bTFE) sequences. Textural features were extracted from the both original and Laplacian of Gaussian (LoG)-filtered MRI images. An automated machine learning algorithm was applied to the extracted feature sets to obtain the optimal preprocessing steps, classification algorithm, and corresponding hyper-parameters. RESULTS: A gradient boosting classifier using all textual features from original and LoG-filtered TSE images and bTFE images identified by the automated machine learning algorithm achieved the optimal performance with sensitivity, specificity, accuracy, and area under ROC curve (AUC) of 100%, 88.5%, 95.2%, and 0.98 in the prediction of placental invasion. In addition, textural features that contributed to the prediction of placental invasion differ from the features significantly affected by normal placenta maturation. CONCLUSIONS: Quantifying intraplacental heterogeneity using LoG filtration and texture analysis highlights the different heterogeneous appearance caused by abnormal placentation relative to normal maturation. The predictive model derived from automated machine learning yielded good performance, indicating the proposed radiomic analysis pipeline can accurately predict placental invasion and facilitate clinical decision-making for pregnant women with suspicious placental invasion. KEY POINTS: • The intraplacental texture features have high efficiency in prediction of invasive placentation after 24 gestational weeks. • The features with dominated predictive power did not overlap with the features significantly affected by gestational age.

Design of a Purely Mechanical Sensor-Controller Integrated System for Walking Assistance on an Ankle-Foot Exoskeleton.

Propulsion during push-off (PO) is a key factor to realize human locomotion. Through the detection of real-time gait stage, assistance could be provided to the human body at the proper time. In most cases, ankle-foot exoskeletons consist of electronic sensors, microprocessors, and actuators. Although these three essential elements contribute to fulfilling the function of the detection, control, and energy injection, they result in a huge system that reduces the wearing comfort. To simplify the sensor-controller system and reduce the mass of the exoskeleton, we designed a smart clutch in this paper, which is a sensor-controller integrated system that comprises a sensing part and an executing part. With a spring functioning as an actuator, the whole exoskeleton system is completely made up of mechanical parts and has no external power source. By controlling the engagement of the actuator based on the signal acquired from the sensing part, the proposed clutch enables the ankle-foot exoskeleton (AFE) to provide additional ankle torque during PO, and allows free rotation of the ankle joint during swing phase, thus reducing the metabolic cost of the human body. There are two striking advantages of the designed clutch. On the one hand, the clutch is lightweight and reliable-it resists the possible shock during walking since there is no circuit connection or power in the system. On the other hand, the detection of gait relies on the contact states between human feet and the ground, so the clutch is universal and does not need to be customized for individuals.

Janus Iron Oxides @ Semiconducting Polymer Nanoparticle Tracer for Cell Tracking by Magnetic Particle Imaging.

Iron oxides nanoparticles tailored for magnetic particle imaging (MPI) have been synthesized, and their MPI signal intensity is three-times that of commercial MPI contrast (Ferucarbotran, also called Vivotrax) and seven-times that of MRI contrast (Feraheme) at the same Fe concentration. MPI tailored iron oxide nanoparticles were encapsulated with semiconducting polymers to produce Janus nanoparticles that possessed optical and magnetic properties for MPI and fluorescence imaging. Janus particles were applied to cancer cell labeling and in vivo tracking, and as few as 250 cells were imaged by MPI after implantation, corresponding to an amount of 7.8 ng of Fe. Comparison with MRI and fluorescence imaging further demonstrated the advantages of our Janus particles for MPI-super sensitivity, unlimited tissue penetration, and linear quantitativity.

A Novel Model to Simulate Flexural Complements in Compliant Sensor Systems.

The main challenge in analyzing compliant sensor systems is how to calculate the large deformation of flexural complements. Our study proposes a new model that is called the spline pseudo-rigid-body model (spline PRBM). It combines dynamic spline and the pseudo-rigid-body model (PRBM) to simulate the flexural complements. The axial deformations of flexural complements are modeled by using dynamic spline. This makes it possible to consider the nonlinear compliance of the system using four control points. Three rigid rods connected by two revolute (R) pins with two torsion springs replace the three lines connecting the four control points. The kinematic behavior of the system is described using Lagrange equations. Both the optimization and the numerical fitting methods are used for resolving the characteristic parameters of the new model. An example is given of a compliant mechanism to modify the accuracy of the model. The spline PRBM is important in expanding the applications of the PRBM to the design and simulation of flexural force sensors.

Design and Optimization of a Novel Three-Dimensional Force Sensor with Parallel Structure.

To measure large external forces exerted on a loading platform, a novel three-dimensional force sensor is developed in this paper. The proposed sensor was designed with a parallel mechanism with three degrees of freedom. Kinematic analysis of this sensor was performed. Due to its structural characteristics, the working principle of the sensor was analyzed using a Jacobian matrix. The sensitivity diversity index and measuring capability were both calculated. The analysis showed that the proposed sensor is more suitable for measuring large forces than existing strain sensors. In addition, compared with existing strain sensors, this sensor is more suitable for measuring forces along the x and y axes. By changing the stiffness coefficients of the springs, the proposed sensor has reconfigurability. This sensor can change its measuring capability to meet different requirements. Next, the mode shapes and natural frequencies of the proposed sensor were performed. Finally, based on these performance indices, the design variables were optimized using a Multi-Objective Genetic Algorithm.