Extremely preterm infants born outside a provincial tertiary perinatal center and transferred postnatally associated with poor outcomes: a real-world observational study

IntroductionExtremely preterm infants (EPIs) have high morbidity and mortality, and are recommended to be born in a tertiary perinatal center (inborn). However, many EPIs in central China are born in lower-level hospitals and transferred postnatally, the outcomes of which remain to be investigated.MethodsEPIs admitted to the Department of Neonatology, Maternal and Child Health Hospital of Hubei Province from January 2013 to December 2022 were retrospectively recruited and divided into the control (inborn) and transfer groups (born in other hospitals). The neonatal and maternal characteristics, neonatal outcomes, and the treatment of survival EPIs were analyzed.ResultsA total of 174 and 109 EPIs were recruited in the control and transfer groups, respectively. EPIs in the transfer group have a higher birth weight and a lower proportion of multiple pregnancies than the control group (all P < 0.05). The proportions of antenatal steroids, magnesium sulfate, cesarean delivery, premature rupture of membranes ≥18 h, gestational diabetes, and amniotic fluid abnormalities were lower in the transfer group (all P < 0.05). Survival rates (64.22% vs. 56.32%), proportions of severe periventricular-intraventricular hemorrhage (PIVH) (11.93% vs. 11.49%), severe bronchopulmonary dysplasia (sBPD) (21.05% vs. 20%), and severe retinopathy of prematurity (ROP) (24.77% vs. 20.11%) were similar in the transfer and control groups (all P > 0.05). However, the transfer group had higher proportions of severe birth asphyxia (34.86% vs. 13.22%, P < 0.001), PIVH (42.20% vs. 29.89%, P = 0.034), and extrauterine growth retardation (EUGR) (17.43% vs. 6.32%, P = 0.003). Less surfactant utilization was found in the transfer group among survival EPIs (70.00% vs. 93.88%, P < 0.001).ConclusionEPIs born outside a tertiary perinatal center and transferred postnatally did not have significantly higher mortality and rates of severe complications (severe PIVH, severe ROP, and sBPD), but there may be an increased risk of severe asphyxia, PIVH and EUGR. This may be due to differences in maternal and neonatal characteristics and management. Further follow-up is needed to compare neurodevelopmental outcomes, and it is recommended to transfer the EPIs in utero to reduce the risk of poor physical and neurological development

Effect of Ultrafast Broadband Nonlinear Optical Responses by Doping Silver into Ti3C2 Nanosheets at Visible Spectra

Ti3C2 nanosheet is a newly discovered two-dimensional (2D) clan. It turns out to have encouraging applications for electromagnetic shielding and energy storage. Here, Ag@ Ti3C2 hybrids are precisely synthesized by using the one-step solution processing method. Also, their ultrafast broadband nonlinear optical responses in the visible region are studied systematically through nanosecond open-aperture Z-scan and transient absorption techniques. The mechanism of two-photon absorption (TPA) is disclosed in the visible region (409–532 nm). When the laser energy is low and the wavelength is longer than 400 nm, nonlinear absorption cannot happen. Meanwhile, as the laser energy increases, two photons will be absorbed by the electrons in the valence band and the electrons will jump to the conduction band. The process is named as two-photon absorption which will make the specimen show reverse saturable absorption (RSA) properties. What is more, the ultrafast carrier dynamics of the specimen are studied by using the transient absorption. The result shows that the decay contains two phases: the fast and then the slow one. The two phases first come from electron–phonon and then from phonon–phonon interactions, respectively. The electron transfer and charge carrier trapping processes are further verified by the outcomes of similar measurements on Ag@ Ti3C2 hybrids. Besides, the two decay processes increase together with the pump fluence. These results show that Ti3C2 nanosheet has potential applications in broadband optical limiter

Deep Learning for Classification of Bone Lesions on Routine MRI

Background: Radiologists have difficulty distinguishing benign from malignant bone lesions because these lesions may have similar imaging appearances. The purpose of this study was to develop a deep learning algorithm that can differentiate benign and malignant bone lesions using routine magnetic resonance imaging (MRI) and patient demographics. Methods: 1,060 histologically confirmed bone lesions with T1- and T2-weighted pre-operative MRI were retrospectively identified and included, with lesions from 4 institutions used for model development and internal validation, and data from a fifth institution used for external validation. Image-based models were generated using the EfficientNet-B0 architecture and a logistic regression model was trained using patient age, sex, and lesion location. A voting ensemble was created as the final model. The performance of the model was compared to classification performance by radiology experts. Findings: The cohort had a mean age of 30±23 years and was 58.3% male, with 582 benign lesions and 478 malignant. Compared to a contrived expert committee result, the ensemble deep learning model achieved (ensemble vs. experts): similar accuracy (0·76 vs. 0·73, p=0·7), sensitivity (0·79 vs. 0·81, p=1·0) and specificity (0·75 vs. 0·66, p=0·48), with a ROC AUC of 0·82. On external testing, the model achieved ROC AUC of 0·79. Interpretation: Deep learning can be used to distinguish benign and malignant bone lesions on par with experts. These findings could aid in the development of computer-aided diagnostic tools to reduce unnecessary referrals to specialized centers from community clinics and limit unnecessary biopsies. Funding: This work was funded by a Radiological Society of North America Research Medical Student Grant (#RMS2013) and supported by the Amazon Web Services Diagnostic Development Initiative

The biogeography of relative abundance of soil fungi versus bacteria in surface topsoil

Fungi and bacteria are the two dominant groups of soil microbial communities worldwide. By controlling the turnover of soil organic matter, these organisms directly regulate the cycling of carbon between the soil and the atmosphere. Fundamental differences in the physiology and life history of bacteria and fungi suggest that variation in the biogeography of relative abundance of soil fungi versus bacteria could drive striking differences in carbon decomposition and soil organic matter formation between different biomes. However, a lack of global and predictive information on the distribution of these organisms in terrestrial ecosystems has prevented the inclusion of relative abundance of soil fungi versus bacteria and the associated processes in global biogeochemical models. Here, we used a global-scale dataset of >3000 distinct observations of abundance of soil fungi versus bacteria in the surface topsoil (up to 15 cm) to generate the first quantitative and high-spatial-resolution (1 km2) explicit map of soil fungal proportion, defined as fungi/fungi + bacteria, across terrestrial ecosystems. We reveal striking latitudinal trends where fungal dominance increases in cold and high-latitude environments with large soil carbon stocks. There was a strong nonlinear response of fungal dominance to the environmental gradient, i.e., mean annual temperature (MAT) and net primary productivity (NPP). Fungi dominated in regions with low MAT and NPP and bacteria dominated in regions with high MAT and NPP, thus representing slow vs. fast soil energy channels, respectively, a concept with a long history in soil ecology. These high-resolution models provide the first steps towards representing the major soil microbial groups and their functional differences in global biogeochemical models to improve predictions of soil organic matter turnover under current and future climate scenarios. Raw datasets and global maps generated in this study are available at https://doi.org/10.6084/m9.figshare.19556419 (Yu, 2022).ISSN:1866-3516ISSN:1866-350