[Impact of different angles of pulmonary surfactant administration on bronchopulmonaryplasia and intracranial hemorrhage in preterm infants: a prospective randomized controlled study]. / ä¸åŒè§’åº¦æ³¨å ¥è‚ºè¡¨é¢æ´»æ€§ç‰©è´¨å¯¹æ—©äº§å„¿æ”¯æ°”ç®¡è‚ºå‘è‚²ä¸è‰¯å’Œé¢ å† å‡ºè¡€çš„å½±å“ï¼šä¸€é¡¹å‰çž»æ€§éšæœºå¯¹ç §ç ”ç©¶.

OBJECTIVES: To investigate the effects of different angles of pulmonary surfactant (PS) administration on the incidence of bronchopulmonary dysplasia and intracranial hemorrhage in preterm infants. METHODS: A prospective study was conducted on 146 preterm infants (gestational age <32 weeks) admitted to the Department of Neonatology, Provincial Hospital Affiliated to Anhui Medical University from January 2019 to May 2023. The infants were randomly assigned to different angles for injection of pulmonary surfactant groups: 0° group (34 cases), 30° group (36 cases), 45° group (38 cases), and 60° group (38 cases). Clinical indicators and outcomes were compared among the groups. RESULTS: The oxygenation index was lower in the 60° group compared with the other three groups, with shorter invasive ventilation time and oxygen use time, and a lower incidence of bronchopulmonary dysplasia than the other three groups (P<0.05). The incidence of intracranial hemorrhage was lower in the 60° group compared to the 0° group (P<0.05). The cure rate in the 60° group was higher than that in the 0° group and the 30° group (P<0.05). CONCLUSIONS: The clinical efficacy of injection of pulmonary surfactant at a 60° angle is higher than other angles, reducing the incidence of intracranial hemorrhage and bronchopulmonary dysplasia in preterm infants.

WiFi Indoor Location Based on Area Segmentation.

Indoor positioning is the basic requirement of future positioning services, and high-precision, low-cost indoor positioning algorithms are the key technology to achieve this goal. Different from outdoor maps, indoor data has the characteristic of uneven distribution and close correlation. In areas with low data density, in order to achieve a high-precision positioning effect, the positioning time will be correspondingly longer, but this is not necessary. The instability of WiFi leads to the introduction of noise when collecting data, which reduces the overall performance of the positioning system, so denoising is very necessary. For the above problems, a positioning system using the DBSCAN algorithm to segment regions and realize regionalized positioning is proposed. DBSCAN algorithm not only divides the dataset into core points and edge points, but also divides part of the data into noise points to achieve the effect of denoising. In the core part, the dimensionality of the data is reduced by using stacking auto-encoders (SAE), and the localization task is accomplished by using a deep neural network (DNN) with an adaptive learning rate. At the edge points, the random forest (RF) algorithm is used to complete the localization task. Finally, the proposed architecture is verified on the UJIIndoorLoc dataset. The experimental results show that our positioning accuracy does not exceed 1.5 m with a probability of less than 87.2% at the edge point, and the time is only 32 ms; the positioning accuracy does not exceed 1.5 m with a probability of less than 98.8% at the core point. Compared with indoor positioning algorithms such as multi-layer perceptron and K Nearest Neighbors (KNN), good results have been achieved.

Interference effect on the Andreev reflections induced by Majorana bound states.

We investigate the effect of quantum interference on the Andreev reflections (ARs) induced by Majorana bound states (MBSs), by considering their additional coupling via a quantum-dot molecule. It is found that due to the direct and indirect couplings of MBSs, a quantum ring is constructed in this system. Consequently, the interference effect makes important contribution to the ARs, especially in the presence of the local magnetic flux. All the results are manifested as the tight dependence of the differential conductance and Fano factors on the magnetic flux phase factor, dot-MBS couplings, and the dot level, respectively. Moreover, at the zero-bias limit, the magnitudes of the Fano factors and their relation can be efficiently altered by the interference properties. We believe that quantum interference is important for manipulating the Andreev reflection behaviors of the MBSs.

Identification of rifampin-regulated functional modules and related microRNAs in human hepatocytes based on the protein interaction network.

BACKGROUND: In combination with gene expression profiles, the protein interaction network (PIN) constructs a dynamic network that includes multiple functional modules. Previous studies have demonstrated that rifampin can influence drug metabolism by regulating drug-metabolizing enzymes, transporters, and microRNAs (miRNAs). Rifampin induces gene expression, at least in part, by activating the pregnane X receptor (PXR), which induces gene expression; however, the impact of rifampin on global gene regulation has not been examined under the molecular network frameworks. METHODS: In this study, we extracted rifampin-induced significant differentially expressed genes (SDG) based on the gene expression profile. By integrating the SDG and human protein interaction network (HPIN), we constructed the rifampin-regulated protein interaction network (RrPIN). Based on gene expression measurements, we extracted a subnetwork that showed enriched changes in molecular activity. Using the Kyoto Encyclopedia of Genes and Genomes (KEGG), we identified the crucial rifampin-regulated biological pathways and associated genes. In addition, genes targeted by miRNAs that were significantly differentially expressed in the miRNA expression profile were extracted based on the miRNA-gene prediction tools. The miRNA-regulated PIN was further constructed using associated genes and miRNAs. For each miRNA, we further evaluated the potential impact by the gene interaction network using pathway analysis. RESULTS AND DISCCUSSION: We extracted the functional modules, which included 84 genes and 89 interactions, from the RrPIN, and identified 19 key rifampin-response genes that are associated with seven function pathways that include drug response and metabolism, and cancer pathways; many of the pathways were supported by previous studies. In addition, we identified that a set of 6 genes (CAV1, CREBBP, SMAD3, TRAF2, KBKG, and THBS1) functioning as gene hubs in the subnetworks that are regulated by rifampin. It is also suggested that 12 differentially expressed miRNAs were associated with 6 biological pathways. CONCLUSIONS: Our results suggest that rifampin contributes to changes in the expression of genes by regulating key molecules in the protein interaction networks. This study offers valuable insights into rifampin-induced biological mechanisms at the level of miRNAs, genes and proteins.

MatPred: Computational Identification of Mature MicroRNAs within Novel Pre-MicroRNAs.

BACKGROUND: MicroRNAs (miRNAs) are short noncoding RNAs integral for regulating gene expression at the posttranscriptional level. However, experimental methods often fall short in finding miRNAs expressed at low levels or in specific tissues. While several computational methods have been developed for predicting the localization of mature miRNAs within the precursor transcript, the prediction accuracy requires significant improvement. METHODOLOGY/PRINCIPAL FINDINGS: Here, we present MatPred, which predicts mature miRNA candidates within novel pre-miRNA transcripts. In addition to the relative locus of the mature miRNA within the pre-miRNA hairpin loop and minimum free energy, we innovatively integrated features that describe the nucleotide-specific RNA secondary structure characteristics. In total, 94 features were extracted from the mature miRNA loci and flanking regions. The model was trained based on a radial basis function kernel/support vector machine (RBF/SVM). Our method can predict precise locations of mature miRNAs, as affirmed by experimentally verified human pre-miRNAs or pre-miRNAs candidates, thus achieving a significant advantage over existing methods. CONCLUSIONS: MatPred is a highly effective method for identifying mature miRNAs within novel pre-miRNA transcripts. Our model significantly outperformed three other widely used existing methods. Such processing prediction methods may provide important insight into miRNA biogenesis.

Crystallographic information of intermediate phases in binary Mg-X (X=Sn, Y, Sc, Ag) alloys.

The compositions and structures of thermodynamically stable or metastable precipitations in binary Mg-X (X=Sn, Y, Sc, Ag) alloys are predicted using ab-initio evolutionary algorithm. The geometry optimizations of the predicted intermetallic compounds are carried out in the framework of density functional theory (DFT) [1]. A complete list of the optimized crystallographic information (in cif format) of the predicted intermetallic phases is presented here. The data is related to "Predictions on the compositions, structures, and mechanical properties of intermediate phases in binary Mg-X (X=Sn, Y, Sc, Ag ) alloys" by Liu et al. [2].

Novel stable hard transparent conductors in TiO2-TiC system: design materials from scratch.

Two new ternary compounds in the TiO2-TiC system, Ti5C2O6 and Ti3C2O2, are reported for the first time based on ab initio evolutionary algorithm. Ti5C2O6 has a tube-structure in which sp(1) hybridized carbon chains run through the lattice along the b-axis; while in the Ti3C2O2 lattice, double TiO6 polyhedral are separated by the non-coplanar sp(2) hybridized hexagon graphite layers along the c-axis, forming a sandwich-like structure. At ambient conditions, the two compounds are found to be mechanically and dynamically stable and intrinsic transparent conductors with high hardness (about twice harder than the conventional transparent conducting oxides). These mechanical, electronic, and optical properties make Ti5C2O6 and Ti3C2O2 ternary compounds be promising robust, hard, transparent, and conductive materials.

Noise-tuning-based hysteretic noisy chaotic neural network for broadcast scheduling problem in wireless multihop networks.

Compared with noisy chaotic neural networks (NCNNs), hysteretic noisy chaotic neural networks (HNCNNs) are more likely to exhibit better optimization performance at higher noise levels, but behave worse at lower noise levels. In order to improve the optimization performance of HNCNNs, this paper presents a novel noise-tuning-based hysteretic noisy chaotic neural network (NHNCNN). Using a noise tuning factor to modulate the level of stochastic noises, the proposed NHNCNN not only balances stochastic wandering and chaotic searching, but also exhibits stronger hysteretic dynamics, thereby improving the optimization performance at both lower and higher noise levels. The aim of the broadcast scheduling problem (BSP) in wireless multihop networks (WMNs) is to design an optimal time-division multiple-access frame structure with minimal frame length and maximal channel utilization. A gradual NHNCNN (G-NHNCNN), which combines the NHNCNN with the gradual expansion scheme, is applied to solve BSP in WMNs to demonstrate the performance of the NHNCNN. Simulation results show that the proposed NHNCNN has a larger probability of finding better solutions compared to both the NCNN and the HNCNN regardless of whether noise amplitudes are lower or higher.

Novel hysteretic noisy chaotic neural network for broadcast scheduling problems in packet radio networks.

Noisy chaotic neural network (NCNN), which can exhibit stochastic chaotic simulated annealing (SCSA), has been proven to be a powerful tool in solving combinatorial optimization problems. In order to retain the excellent optimization property of SCSA and improve the optimization performance of the NCNN using hysteretic dynamics without increasing network parameters, we first construct an equivalent model of the NCNN and then control noises in the equivalent model to propose a novel hysteretic noisy chaotic neural network (HNCNN). Compared with the NCNN, the proposed HNCNN can exhibit both SCSA and hysteretic dynamics without introducing extra system parameters, and can increase the effective convergence toward optimal or near-optimal solutions at higher noise levels. Broadcast scheduling problem (BSP) in packet radio networks (PRNs) is to design an optimal time-division multiple-access (TDMA) frame structure with minimal frame length, maximal channel utilization, and minimal average time delay. In this paper, the proposed HNCNN is applied to solve BSP in PRNs to demonstrate its performance. Simulation results show that the proposed HNCNN with higher noise amplitudes is more likely to find an optimal or near-optimal TDMA frame structure with a minimal average time delay than previous algorithms.

[Liver regenerative capacity after partial hepatectomy in rats with nonalcoholic fatty liver disease].

OBJECTIVE: To explore the changes of liver regeneration after partial hepatectomy on rats with nonalcoholic fatty liver disease (NAFLD) caused by a high fat diet. METHODS: One hundred Wistar rats were randomly divided into a control group (group C, n = 45), fed with normal diet, and a NAFLD group, fed with fat-rich diet (group F, n = 55). All rats had a 70% partial hepatectomy at the end of the 12th week. They were sacrificed at postoperative 0, 1, 12, 24, or 36 hours and the percentages of their regenerated liver masses were calculated. The mitosis index was measured microscopically and the changes of cell ultrastructure were observed under an electron microscope. The expression of proliferating cell nuclear antigen (PCNA) was detected using immunohistochemistry. The expression of mRNA of cyclin D1 was measured by RT-PCR. RESULTS: The light and electron microscopy showed that the hepatic sinusoids expanded at an early period after the partial hepatectomy. The mitochondria and rough endoplasmic reticulum (RER) expanded and their number increased. The mitosis index was increased. The sinusoids of the livers in group F were narrow and irregular. The nuclei were smaller and the necrotic cells increased. As compared with the control group, the mitosis index was significantly decreased (P < 0.01), and the regenerative liver weight ratio in group F was lower at postoperative 12 h, 24 h, 36 h (P < 0.01). PCNA labeling index in group F also was lower than that in group C. The peak of the PCNA in group F was later than that of the control group (P < 0.01). In group C, the mRNA of cyclin D1 peaked at the 24th hour after the partial hepatectomy, and then decreased afterwards. In group F, it was lower than that of group C at the same time (P < 0.01). CONCLUSION: After NAFLD rats had partial hepatectomies, the capacity of their liver regeneration decreased and the peak of DNA synthesis was delayed, and at the same time the morbidity of the rats increased.