[Risk factors for bronchopulmonary dysplasia in twin preterm infants: a multicenter study]. / åŒèƒŽæ—©äº§å„¿æ”¯æ°”ç®¡è‚ºå‘è‚²ä¸è‰¯å±é™©å› ç´ åˆ†æžï¼šä¸€é¡¹å¤šä¸­å¿ƒç ”ç©¶.

OBJECTIVES: To investigate the risk factors for bronchopulmonary dysplasia (BPD) in twin preterm infants with a gestational age of <34 weeks, and to provide a basis for early identification of BPD in twin preterm infants in clinical practice. METHODS: A retrospective analysis was performed for the twin preterm infants with a gestational age of <34 weeks who were admitted to 22 hospitals nationwide from January 2018 to December 2020. According to their conditions, they were divided into group A (both twins had BPD), group B (only one twin had BPD), and group C (neither twin had BPD). The risk factors for BPD in twin preterm infants were analyzed. Further analysis was conducted on group B to investigate the postnatal risk factors for BPD within twins. RESULTS: A total of 904 pairs of twins with a gestational age of <34 weeks were included in this study. The multivariate logistic regression analysis showed that compared with group C, birth weight discordance of >25% between the twins was an independent risk factor for BPD in one of the twins (OR=3.370, 95%CI: 1.500-7.568, P<0.05), and high gestational age at birth was a protective factor against BPD (P<0.05). The conditional logistic regression analysis of group B showed that small-for-gestational-age (SGA) birth was an independent risk factor for BPD in individual twins (OR=5.017, 95%CI: 1.040-24.190, P<0.05). CONCLUSIONS: The development of BPD in twin preterm infants is associated with gestational age, birth weight discordance between the twins, and SGA birth.

Classification of high-grade glioblastoma and single brain metastases using a new SCAT-inception model trained with MRI images.

Background and objectives: Glioblastoma (GBM) and brain metastasis (MET) are the two most common intracranial tumors. However, the different pathogenesis of the two tumors leads to completely different treatment options. In terms of magnetic resonance imaging (MRI), GBM and MET are extremely similar, which makes differentiation by imaging extremely challenging. Therefore, this study explores an improved deep learning algorithm to assist in the differentiation of GBM and MET. Materials and methods: For this study, axial contrast-enhanced T1 weight (ceT1W) MRI images from 321 cases of high-grade gliomas and solitary brain metastasis were collected. Among these, 251 out of 270 cases were selected for the experimental dataset (127 glioblastomas and 124 metastases), 207 cases were chosen as the training dataset, and 44 cases as the testing dataset. We designed a new deep learning algorithm called SCAT-inception (Spatial Convolutional Attention inception) and used five-fold cross-validation to verify the results. Results: By employing the newly designed SCAT-inception model to predict glioblastomas and brain metastasis, the prediction accuracy reached 92.3%, and the sensitivity and specificity reached 93.5 and 91.1%, respectively. On the external testing dataset, our model achieved an accuracy of 91.5%, which surpasses other model performances such as VGG, UNet, and GoogLeNet. Conclusion: This study demonstrated that the SCAT-inception architecture could extract more subtle features from ceT1W images, provide state-of-the-art performance in the differentiation of GBM and MET, and surpass most existing approaches.

Mutual-Attention Net: A Deep Attentional Neural Network for Keyphrase Generation.

Neural keyphrase generation (NKG) is a recently proposed approach to automatically extract keyphrase from a document. Unlike the traditional keyphrase extraction, the NKG can generate keyphrases that do not appear in the document. However, as a supervised method, NKG is hindered by noise. In order to solve the problem that the existing NKG model does not consider denoising the source document, in this work, this paper introduces a new denoising architecture mutual-attention network (MA-net). Considering the structure of documents in popular datasets, the multihead attention is applied to dig out the relevance between title and abstract, which aids denoising. To further accurate generation of high-quality keyphrases, we use multihead attention to compute the content vector instead of Bahdanau attention. Finally, we employ a hybrid network that augments the proposed architecture to solve OOV (out-of-vocabulary) problem. It can not only generate words from the decoder but also copy words from the source document. Evaluation using five benchmark datasets shows that our model significantly outperforms the state-of-the-art ones currently in the research field.

Exploring Adaptive Graph Topologies and Temporal Graph Networks for EEG-Based Depression Detection.

In recent years, Graph Neural Networks (GNNs) based on deep learning techniques have achieved promising results in EEG-based depression detection tasks but still have some limitations. Firstly, most existing GNN-based methods use pre-computed graph adjacency matrices, which ignore the differences in brain networks between individuals. Additionally, methods based on graph-structured data do not consider the temporal dependency information of brain networks. To address these issues, we propose a deep learning algorithm that explores adaptive graph topologies and temporal graph networks for EEG-based depression detection. Specifically, we designed an Adaptive Graph Topology Generation (AGTG) module that can adaptively model the real-time connectivity of the brain networks, revealing differences between individuals. In addition, we designed a Graph Convolutional Gated Recurrent Unit (GCGRU) module to capture the temporal dynamical changes of brain networks. To further explore the differential features between depressed and healthy individuals, we adopt Graph Topology-based Max-Pooling (GTMP) module to extract graph representation vectors accurately. We conduct a comparative analysis with several advanced algorithms on both public and our own datasets. The results reveal that our final model achieves the highest Area Under the Receiver Operating Characteristic Curve (AUROC) on both datasets, with values of 83% and 99%, respectively. Furthermore, we perform extensive validation experiments demonstrating our proposed method's effectiveness and advantages. Finally, we present a comprehensive discussion on the differences in brain networks between healthy and depressed individuals based on the outputs of our final model's AGTG and GTMP modules.

Finite-time cluster synchronization for complex dynamical networks under FDI attack: A periodic control approach.

In this paper, the finite-time cluster synchronization problem is addressed for complex dynamical networks (CDNs) with cluster characteristics under false data injection (FDI) attacks. A type of FDI attack is taken into consideration to reflect the data manipulation that controllers in CDNs may suffer. In order to improve the synchronization effect while reducing the control cost, a new periodic secure control (PSC) strategy is proposed in which the set of pinning nodes changes periodically. The aim of this paper is to derive the gains of the periodic secure controller such that the synchronization error of the CDN remains at a certain threshold in finite time with the presence of external disturbances and false control signals simultaneously. Through considering the periodic characteristics of PSC, a sufficient condition is obtained to guarantee the desired cluster synchronization performance, based on which the gains of the periodic cluster synchronization controllers are acquired by resolving an optimization problem proposed in this paper. A numerical case is carried out to validate the cluster synchronization performance of the PSC strategy under cyber attacks.

Short term outcomes of extremely low birth weight infants from a multicenter cohort study in Guangdong of China.

With the increase in extremely low birth weight (ELBW) infants, their outcome attracted worldwide attention. However, in China, the related studies are rare. The hospitalized records of ELBW infants discharged from twenty-six neonatal intensive care units in Guangdong Province of China during 2008-2017 were analyzed. A total of 2575 ELBW infants were enrolled and the overall survival rate was 55.11%. From 2008 to 2017, the number of ELBW infants increased rapidly from 91 to 466, and the survival rate improved steadily from 41.76% to 62.02%. Increased survival is closely related to birth weight (BW), regional economic development, and specialized hospital. The incidence of complications was neonatal respiratory distress syndrome (85.2%), oxygen dependency at 28 days (63.7%), retinopathy of prematurity (39.3%), intraventricular hemorrhage (29.4%), necrotizing enterocolitis (12.0%), and periventricular leukomalacia (8.0%). Among the 1156 nonsurvivors, 90.0% of infants died during the neonatal period (≤ 28 days). A total of 768 ELBW infants died after treatment withdrawal, for reasons of economic and/or poor outcome. The number of ELBW infants is increasing in Guangdong Province of China, and the overall survival rate is improving steadily.

Clinical treatment outcomes and their changes in extremely preterm twins: a multicenter retrospective study in Guangdong Province, China. / è¶ æœªæˆç†ŸåŒèƒŽå„¿ä¸´åºŠæ•‘æ²»ç»“å±€åŠå˜åŒ–åˆ†æžï¼šä¸€é¡¹å¹¿ä¸œçœå¤šä¸­å¿ƒå›žé¡¾æ€§ç ”ç©¶.

OBJECTIVES: To investigate the clinical treatment outcomes and the changes of the outcomes over time in extremely preterm twins in Guangdong Province, China. METHODS: A retrospective analysis was performed for 269 pairs of extremely preterm twins with a gestational age of <28 weeks who were admitted to the department of neonatology in 26 grade A tertiary hospitals in Guangdong Province from January 2008 to December 2017. According to the admission time, they were divided into two groups: 2008-2012 and 2013-2017. Besides, each pair of twins was divided into the heavier infant and the lighter infant subgroups according to birth weight. The perinatal data of mothers and hospitalization data of neonates were collected. The survival rate of twins and the incidence rate of complications were compared between the 2008-2012 and 2013-2017 groups. RESULTS: Compared with the 2008-2012 group, the 2013-2017 group (both the heavier infant and lighter infant subgroups) had lower incidence rates of severe asphyxia and smaller head circumference at birth (P<0.05). The mortality rates of both of the twins, the heavier infant of the twins, and the lighter infant of the twins were lower in the 2013-2017 group compared with the 2008-2012 group (P<0.05). Compared with the 2008-2012 group, the 2013-2017 group (both the heavier infant and lighter infant subgroups) had lower incidence rates of pulmonary hemorrhage, patent ductus arteriosus (PDA), periventricular-intraventricular hemorrhage (P-IVH), and neonatal respiratory distress syndrome (NRDS) and a higher incidence rate of bronchopulmonary dysplasia (P<0.05). CONCLUSIONS: There is a significant increase in the survival rate over time in extremely preterm twins with a gestational age of <28 weeks in the 26 grade A tertiary hospitals in Guangdong Province. The incidences of severe asphyxia, pulmonary hemorrhage, PDA, P-IVH, and NRDS decrease in both the heavier and lighter infants of the twins, but the incidence of bronchopulmonary dysplasia increases. With the improvement of diagnosis and treatment, the multidisciplinary collaboration between different fields of fetal medicine including prenatal diagnosis, obstetrics, and neonatology is needed in the future to jointly develop management strategies for twin pregnancy.

3D Hand Pose Estimation Based on Five-Layer Ensemble CNN.

Estimating accurate 3D hand pose from a single RGB image is a highly challenging problem in pose estimation due to self-geometric ambiguities, self-occlusions, and the absence of depth information. To this end, a novel Five-Layer Ensemble CNN (5LENet) is proposed based on hierarchical thinking, which is designed to decompose the hand pose estimation task into five single-finger pose estimation sub-tasks. Then, the sub-task estimation results are fused to estimate full 3D hand pose. The hierarchical method is of great benefit to extract deeper and better finger feature information, which can effectively improve the estimation accuracy of 3D hand pose. In addition, we also build a hand model with the center of the palm (represented as Palm) connected to the middle finger according to the topological structure of hand, which can further boost the performance of 3D hand pose estimation. Additionally, extensive quantitative and qualitative results on two public datasets demonstrate the effectiveness of 5LENet, yielding new state-of-the-art 3D estimation accuracy, which is superior to most advanced estimation methods.

Naoxintong Capsule Inhibits the Development of Cardiovascular Pathological Changes in Bama Minipig Through Improving Gut Microbiota.

Naoxintong capsule (NXT), a Chinese medicine, has performed excellent effects on the prevention and treatment against cardiovascular diseases. NXT is a fine powder mixture without any herb extraction, and there must be lots of ingredients hard to be absorbed. However, little is known about the correlation between the NXT's cardioprotective effects and gut microbiota. Herein, we report the effect of NXT on the development of cardiovascular diseases and clarify the correlation between NXT's cardioprotective effects and gut microbiota. In the current study, minipigs were selected and fed with high-fat diet and NXT daily for successive 8 months. During the process, up to 18 biomedical parameters were monthly determined to observe the dynamic changes after NXT treatment. At the end of experimental process, pathological examinations of heart, coronary artery, carotid artery, thoracic aorta, and abdominal aorta were conducted by HE staining and 16SrDNA sequencing, and analyzing of gut microbiota were conducted. Our results showed that NXT's effects against cardiovascular diseases were through regulating blood lipid profiles, inhibiting vascular inflammation, enhancing antioxidant capacity, and alleviating myocardial injury, without damages on liver and kidney particularly. Concurrently, we also found that long-term administration of NXT increased the diversity of gut microbiota, influenced the microbiome structure and composition stably, and revered the increase of the ratio of the Firmicutes to Bacteroidetes (F/B ratio) in relative abundance. Specifically, our results revealed some key bacterium of Caproiciproducens (enhanced), Sutterella (enhanced), Erysipelotrichaceae (enhanced), and Romboutsia (decreased) that were closely involved in NXT's effects. Taken together, our study demonstrates that NXT can inhibit the development of cardiovascular diseases by ameliorating high-fat diet-induced metabolic disorders and partly through improving gut microbiota.

Pharmacodynamic effects of Dan-hong injection in rats with blood stasis syndrome.

Dan-hong injection (DHI) is extracted from Salvia miltiorrhiza (SM) and Carthamus tinctorius (CT) and is widely used for the treatment of cardiovascular diseases. Our previous results showed DHI could improve hemorheology in rats. Since complex cellular interactions such as inflammation and oxidative stress are believed to be implicated in the pathogenesis of cardiovascular events, investigation of such pathological factors will contribute substantially to the understanding of the features and mechanisms of DHI. Therefore, in this study we used a rat model of blood stasis to explore the overall effects of DHI by detecting twenty three indexes, which were related to inflammation, immune response, vascular endothelial function, myocardial energy metabolism, oxidative stress, platelet aggregation, liver and renal function. Meanwhile, the interaction between SM and CT was discussed by comparing the effects of each single herb. DHI could significantly decrease the serum contents of IL-1ß, TNF-α, IL-6, IL-8, IgM, IgG, IgA, MPO, hs-CRP, MDA, LDH, CK-MB, PAF, ALP and Cr, while elevate NO, SOD, TP and UA levels, indicating that DHI could inhibit inflammation and platelet aggregation, thereby relieving immune response and peroxidation, protecting vascular endothelial and organ function, and then prevent and treat cardiovascular diseases. In terms of compatibility, SM and CT showed complementary effects on markers of inflammatory and oxidative status, vascular endothelial damage and myocardial energy metabolism. On the other hand, they counteracted each other and SM reduced the side effects of creatinine caused by CT. This study contributes to comprehensively understand the pharmacodynamics effects and mechanism of DHI.

Mechanism of Apoptosis Induction by Mycoplasmal Nuclease MGA_0676 in Chicken Embryo Fibroblasts.

MGA_0676 has been characterized as a Mycoplasma gallisepticum nuclease that can induce apoptosis of chicken cells. However, the mechanism by which MGA_0676 induces apoptosis has remained unclear. In this study, we evaluated MGA_0676-induced apoptosis and internalization in immortalized chicken embryo fibroblasts (DF-1) and cancer cell lines. The internalization of MGA_0676 was proven through caveolin-mediated endocytosis by blocking the endocytosis with specific inhibitors or with siRNA. We identified the Thif domain of NEDD8-activating enzyme E1 regulatory subunit (NAE) in DF-1 as the target region interacting with the SNC domain of MGA_0676. The interaction between the Thif and SNC domains was observed co-located in the perinuclear and nuclear of DF-1. We found that the interaction between NAE and MGA_0676 increased the ability of apoptosis and accelerated the process of cullin neddylation in DF-1 cells, in turn activating NF-κB. This resulted in the observed aggregation of NF-κB in the nuclei of DF-1 cells. Moreover, the apoptosis induced by MGA_0676 decreased significantly when NF-κB was inhibited by siRNA or BAY 11-7082 or when NAE was silenced by siRNA. Overall, our results demonstrate that MGA_0676 is internalized through caveolin-mediated endocytosis, interacts with SNC-dependent Thif to accelerate the process of cullin neddylation and activates NF-κB in DF-1 cells, ultimately playing a key role in apoptosis in chicken cells. Our results indicate MGA_0676 constitutes a critical etiological virulence factor of the respiratory disease caused by M. gallisepticum. This study also opens a venue to investigate MGA_0676 as a potential candidate as pro-apoptotic drug in cancer studies.

[Acupuncture with Point Location-a mandatory examination for American NCCAOM certification of acupuncture and oriental medicine].

Acupuncture with Point Location is one of the mandatory examinations for the Diplomate of Oriental Medicine (Dipl.OM.) or Acupuncture (Dipl. Ac.) by American National Certification Commission for Acupuncture and Oriental Medicine (NCCAOM). In reference to NCCAOM Certification Handbook, Acupuncture with Point Location Expanded Content Outline, and Study Guide for Diplomates in Acupuncture Certification, the authors introduced the examination pattern and examination-related contents including such aspects as safety and professional responsibilities, treatment plan, and point location and discussed additionally the enlightening effects on acupuncture practice and examination in universities and international associations of Chinese medicine in our country.

Determination of polycyclic aromatic hydrocarbons in water by a novel mesoporous-coated stainless steel wire microextraction combined with HPLC.

A novel mesoporous-coated stainless steel wire microextraction coupled with the HPLC procedure for quantification of four polycyclic aromatic hydrocarbons in water has been developed, based on the sorption of target analytes on a selectively adsorptive fiber and subsequent desorption of analytes directly into HPLC. Phenyl-functionalized mesoporous materials (Ph-SBA-15) were synthesized and coated on the surfaces of a stainless steel wire. Due to the high porosity and large surface area of the Ph-SBA-15, high extraction efficiency is expected. The influence of various parameters on polycyclic aromatic hydrocarbons extraction efficiency were thoroughly studied and optimized (such as the extraction temperature, the extraction time, the desorption time, the stirring rate and the ionic strength of samples). The results showed that each compound for the analysis of real water samples was tested under optimal conditions with the linearity ranging from 1.02×10(-3) to 200 µg/ L and the detection limits were found from 0.32 to 2.44 ng/ L, respectively. The RSD of the new method was smaller than 4.10%.

Protective action of acupuncture and moxibustion on gastric mucosa in model rats with chronic atrophic gastritis.

OBJECTIVE: To probe the mechanism of acupuncture and moxibustion in atrophic gastritis so as to provide a basis for clinical treatment. METHOD: Observe the effects of acupuncture and moxibustion at the points of Zusanli, Zhongwan and Tianshu on gastric mucosa in model rats with chronic atrophic gastritis. RESULTS: Acupuncture and moxibustion can increase the contents of PGE2alpha, PGF2alpha and cAMP, and decrease the content of cGMP in the tissue of gastric mucosa. CONCLUSION: Acupuncture and moxibustion shows cytoprotection on gastric mucosa, so it is an effective method for treating chronic atrophic gastritis.