Molybdenum Concentration and the Risk of Spontaneous Preterm Birth: A Nested Case-Control Study - Beijing Municipality, China, 2018-2020.

What is already known about this topic?: The level of molybdenum (Mo) in a mother's urine has been linked to the growth rate of the fetus and the blood pressure levels in children. What is added by this report?: We evaluated the variations in maternal plasma Mo concentrations throughout pregnancy and their potential association with the risk of spontaneous preterm birth (SPB). What are the implications for public health practice?: Future research must determine the Mo levels in pregnant women across various regions in China. Moreover, particular attention needs to be given to the potential increase in Mo concentration throughout pregnancy and its possible adverse impacts on the health of both the mother and the fetus.

Co-exposure to phthalates and polycyclic aromatic hydrocarbons and the risk of gestational hypertension in Chinese women.

Phthalates (PAEs) and polycyclic aromatic hydrocarbons (PAHs) are frequently detected in females of reproductive age. Many studies have found that environmental PAE and PAH levels are independent risk factors for gestational hypertension. However, exposure to both components is a more realistic scenario. To better assess the health effects of PAEs and PAHs in pregnant women, we explored the associations of exposure to both individual and combined PAEs and PAHs with gestational hypertension. This nested case-control study was a component of a prospective cohort study conducted in Beijing, China. We included 206 women with gestational hypertension and 214 pregnant controls. We used gas chromatography/tandem mass spectrometry (GC-MS/MS) to detect 8 PAEs and 13 PAHs in > 80 % of all collected hair samples. Multiple linear regression models were employed to test the individual associations between each component and gestational hypertension. A quantile-based g-computation (qgcomp) model and a weighted quantile sum (WQS) regression model were used to estimate whether exposure to both PAEs and PAHs increased the risk of gestational hypertension. The individual exposure analyses revealed that diethyl phthalate (DEP), diisobutyl phthalate (DIBP) (both PAEs), benzo(k)fluoranthene (BKF), anthracene, (ANT), and benzo(a)pyrene (BAP) (all PAHs) were positively associated with increased risk of gestational hypertension. In mixed-effect analyses, the qgcomp model indicated that co-exposure to PAEs and PAHs increased the risk of gestational hypertension (odds ratio = 2.01; 95 % confidence interval: 1.02, 3.94); this finding was verified by the WQS regression model. Our findings support earlier evidence that both PAEs and PAHs increase the risk of gestational hypertension, both individually and in combination. This suggests that reductions in exposure to endocrine system-disrupting chemicals such as PAEs and PAHs might reduce the risk of gestational hypertension.

Maternal cobalt concentration and risk of spontaneous preterm birth: the role of fasting blood glucose and lipid profiles.

Introduction: Spontaneous preterm birth (SPB) is a significant cause of neonatal mortality, yet its etiology remains unclear. Cobalt, an essential trace element, might be a risk factor for SPB. This study aims to investigate the relationship between maternal serum cobalt concentration and SPB, and to clarify the role of blood lipids and fasting blood glucose (FBG) in this relationship. Methods: We conducted a nested case-control study within the Beijing Birth Cohort Study. Serum samples were obtained from 222 pregnant women with SPB and 224 controls during the first (7-13 weeks of pregnancy) and third trimesters (32-42 weeks of pregnancy). Serum cobalt concentration was determined using inductively coupled plasma mass spectrometry (ICP-MS). Fasting blood glucose and lipids levels were detected using a fully automated biochemical immunoassay instrument. Logistic regression models and linear regression models were established to explore the association between serum cobalt concentration and the risk of SPB in pregnant women, and to test the mediating effect of fasting blood glucose (FBG) and lipids. Results: We found that the serum cobalt concentration in mothers with SPB and controls was similar in the first trimester, with values of 0.79 (0.58-1.10) ng/mL and 0.75 (0.51-1.07) ng/mL, respectively. However, in the third trimester, the cobalt concentration increased to 0.88 (0.59-1.14) ng/mL and 0.84 (0.52-1.19) ng/mL, respectively. In the logistic regression model, when considering the third trimester of pregnancy, after adjusting for ethnicity, pre-pregnancy body mass index (BMI), maternal age, education, income, and parity, it was observed that the medium level of cobalt concentration (0.63-1.07 ng/ml) had a negative correlation with the risk of SPB. The odds ratio (OR) was 0.56, with a 95% confidence interval of 0.34-0.90 ng/mL and a p-value of 0.02. This suggests that cobalt in this concentration range played a protective role against SPB. Additionally, it was found that FBG in the third trimester of pregnancy had a partial intermediary role, accounting for 9.12% of the association. However, no relationship between cobalt and SPB risk was found in the first trimester. Conclusion: During the third trimester, intermediate levels of maternal cobalt appear to offer protection against SPB, with FBG playing a partial mediating role. To further clarify the optimal cobalt concentrations during pregnancy for different populations, a multi-center study with a larger sample size is necessary. Additionally, exploring the specific mechanism of FBG's mediating role could provide valuable insights for improving the prevention of SPB.

Characterization and functional analysis of SOCS9 from orange-spotted grouper (Epinephelus coioides) during virus infection.

The suppressor of cytokine signaling (SOCS) proteins family have twelve members including eight known mammalian SOCS members (CISH, SOCS1-7) and four new discovery members (SOCS3b, SOCS5b, SOCS8 and SOCS9) that is regarded as a classic feedback inhibitor of cytokine signaling. Although the function of the mammalian SOCS proteins have been well studied, little is known about the roles of SOCS in fish during viral infection. In this study, the molecular characteristics of SOCS9 from orange-spotted grouper (Epinephelus coioides, EcSOCS9) is investigated. The EcSOCS9 protein encoded 543 amino acids with typical SH2 (389-475aa) and SOCS_box (491-527aa), sharing high identities with reported fish SOCS9. EcSOCS9 was expressed in all detected tissues and highly expressed in kidney. After red-spotted grouper nervous necrosis virus (RGNNV) infection, the expression of EcSOCS9 was significantly induced in vitro. Furthermore, EcSOCS9 overexpression enhanced RGNNV replication, promoted virus-induced mitophagy that evidenced by the increased level of LC3-Ⅱ, BCL2, PGAM5 and decreased level of BNIP3 and FUNDC1. Besides, EcSOCS9 overexpression suppressed the expression levels of ATP6, CYB, ND4, ATP level and induced ROS level. The expression levels of interferon (IFN) related factors (IRF1, IRF3, IRF7, P53), inflammatory factors (IL1-ß, IL8, TLR2, TNF-α) and IFN-3, ISRE, NF-κB, AP1 activities were also reduced by overexpressing EcSOCS9. These date suggests that EcSOCS9 impacts RGNNV infection through modulating mitophagy, regulating the expression levels of IFN- related and inflammatory factors, which will expand our understanding of fish immune responses during viral infection.

MSS-UNet: A Multi-Spatial-Shift MLP-based UNet for skin lesion segmentation.

Multilayer perceptron (MLP) networks have become a popular alternative to convolutional neural networks and transformers because of fewer parameters. However, existing MLP-based models improve performance by increasing model depth, which adds computational complexity when processing local features of images. To meet this challenge, we propose MSS-UNet, a lightweight convolutional neural network (CNN) and MLP model for the automated segmentation of skin lesions from dermoscopic images. Specifically, MSS-UNet first uses the convolutional module to extract local information, which is essential for precisely segmenting the skin lesion. We propose an efficient double-spatial-shift MLP module, named DSS-MLP, which enhances the vanilla MLP by enabling communication between different spatial locations through double spatial shifts. We also propose a module named MSSEA with multiple spatial shifts of different strides and lighter external attention to enlarge the local receptive field and capture the boundary continuity of skin lesions. We extensively evaluated the MSS-UNet on ISIC 2017, 2018, and PH2 skin lesion datasets. On three datasets, the method achieves IoU metrics of 85.01%±0.65, 83.65%±1.05, and 92.71%±1.03, with a parameter size and computational complexity of 0.33M and 15.98G, respectively, outperforming most state-of-the-art methods.The code is publicly available at https://github.com/AirZWH/MSS-UNet.

Functional properties of ATPIF1 in the orange-spotted grouper (Epinephelus coioides) in response to viral infection.

ATP synthase inhibitory factor 1 (ATPIF1) can activate mitochondrial autophagic pathway and mediates immune response by regulating ATP synthase activity. However, the role of fish ATPIF1 on viral infection is still unknown. In this study, we identified an ATPIF1 homolog (Ec-ATPIF1) from orange-spotted grouper (Epinephelus coioides). Ec-ATPIF1 is mainly expressed in the kidney and liver. The expression of Ec-ATPIF1 was significantly up-regulated after RGNNV stimulation in vitro. Further experiments showed that overexpression of Ec-ATPIF1 inhibited the expression of viral genes (CP and RdRp) and intracellular ATP synthesis. Ec-ATPIF1 overexpression also promoted the expression of mitophagy related genes (PINK1, Parkin, BNIP3, NIX, FUNDC1, LC3), inflammation-related factors (IL-1ß, IL-6, IL-8, IL-10, TNF-α, TLR2) and interferon pathway factors (IRF1, IRF3, IRF7, MX1, ISG15, ISG56, MDA5, TRIF). While the knockdown of Ec-ATPIF1 exhibited the opposite effects on the expression of viral genes and immune-related factors above. These data suggest that Ec-ATPIF1 can impact viral infection by regulating mitophagy, ATP synthesis, the expression of inflammatory factors and interferon pathway factors. These findings will be beneficial to better explore the immune regulatory mechanisms of fish respond to viral infection.

Association between light rare earth elements in maternal plasma and the risk of spontaneous preterm birth: a nested case-control study from the Beijing birth cohort study.

BACKGROUND: Parental exposure to rare earth elements (REEs) could increase the risk of premature rupture of membranes, a major cause of spontaneous preterm birth (SPB). In addition, different subtypes of SPB, such as spontaneous preterm labor (SPL) and preterm premature rupture of membranes (PPROM), may have different susceptibility to environmental exposure. Therefore, we investigated the potential associations between REE exposure in different trimesters and SPB and its subtypes. METHODS: A nested case-control study was performed. We included 244 women with SPB as cases and 244 women with full-term delivery as controls. The plasma concentrations of light REEs were measured in the first and third trimesters. Logistic regression was used to analyze the associations between single REE levels and SPB, and Bayesian kernel machine regression (BKMR) was used to analyze the mixed-exposure effect. RESULTS: Exposure to light REEs was associated with SPB and its subtypes only in the third trimester. Specifically, the intermediate- and highest-tertile concentration groups of La and the highest-tertile concentration group of Sm were associated with an increased risk of SPL, with adjusted odds ratios (AORs) of 2.00 (95% CIs: 1.07-3.75), 1.87 (95% CIs: 1.01-3.44), and 1.82 (95% CIs: 1.00-3.30), respectively. The highest-tertile concentration group of Pr was associated with an increased risk of PPROM, with an AOR of 1.69 (95% CIs: 1.00-2.85). Similar results were also found in BKMR models. CONCLUSIONS: La and Sm levels in plasma may be associated with the risk of SPL, and Pr levels in plasma may be associated with the risk of PPROM.

Dual Inhibition of Mycobacterium tuberculosis and the Host TGFBR1 by an Anilinoquinazoline.

Tuberculosis (TB) control is complicated by the emergence of drug resistance. Promising strategies to prevent drug resistance are the targeting of nonreplicating, drug-tolerant bacterial populations and targeting of the host, but inhibitors and targets for either are still rare. In a cell-based screen of ATP-competitive inhibitors, we identified compounds with in vitro activity against replicating Mycobacterium tuberculosis (Mtb), and an anilinoquinazoline (AQA) that also had potent activity against nonreplicating and persistent Mtb. AQA was originally developed to inhibit human transforming growth factor receptor 1 (TGFBR1), a host kinase that is predicted to have host-adverse effects during Mtb infection. The structure-activity relationship of this dually active compound identified the pyridyl-6-methyl group as being required for potent Mtb inhibition but a liability for P450 metabolism. Pyrrolopyrimidine (43) emerged as the optimal compound that balanced micromolar inhibition of nonreplicating Mtb and TGFBR1 while also demonstrating improved metabolic stability and pharmacokinetic profiles.

[Effect of early off-bed mobility on diaphragm function in intensive care unit patients undergoing mechanical ventilation].

OBJECTIVE: To explore the improvement of diaphragm function after early off-bed mobility intervention in intensive care unit (ICU) patients undergoing mechanical ventilation. METHODS: A randomized controlled trial was conducted. A total of 147 adult patients undergoing mechanical ventilation admitted to ICU of Affiliated Hospital of Zunyi Medical University from October 2019 to March 2022 were enrolled. The patients were divided into control group and observation group by convenient sampling. Except for the different intervention programs of early mobility, other treatment and nursing of the patients in the two groups were carried out according to ICU routine. Progressive early activities were performed in the control group, while early off-bed mobility was performed in the observation group. The changes of diaphragm thickness at the end of inspiratory (DTei), diaphragm thickness at the end of expiratory (DTee) and diaphragm thickening fraction (DTF) before and 24, 48, 72 and 96 hours of intervention, and the duration of mechanical ventilation, length of ICU stay and 24-hour re-intubation rate after intervention were compared between the two groups. RESULTS: Among the 147 patients, there were 4 cases of detachment in the control group and 5 cases of detachment in the observation group. Finally, 138 patients were enrolled, 69 cases in the control group and 69 cases in the observation group. There was no significant difference in gender, age, diagnosis of ICU, sedatives, muscle strength, ventilator model, acute physiology and chronic health evaluation II (APACHE II) score and DTei, DTee, DTF before intervention between the two groups. The DTei, DTee and DTF in both groups were increased gradually with the extension of intervention time, especially in the observation group [DTei (cm) at 24, 48, 72 and 96 hours of intervention in the observation group were 0.247±0.014, 0.275±0.016, 0.300±0.013 and 0.329±0.013, while in the control group were 0.242±0.015, 0.258±0.013, 0.269±0.014, and 0.290±0.017, effect of time: F = 993.825, P = 0.000, effect of intervention: F = 82.304, P = 0.000, interaction effect between intervention and time: F = 84.457, P = 0.000; DTee (cm) of the observation group were 0.213±0.014, 0.227±0.013, 0.243±0.016, 0.264±0.010, while in the control group were 0.213±0.016, 0.218±0.013, 0.224±0.013, 0.234±0.014, effect of time: F = 385.552, P = 0.000, effect of intervention: F = 28.161, P = 0.000, interaction effect between intervention and time: F = 45.012, P = 0.000; DTF of the observation group were (15.98±4.23)%, (21.35±4.67)%, (24.09±4.44)% and (25.24±3.74)%, while in the control group were (14.17±4.66)%, (18.11±3.92)%, (20.22±4.19)% and (20.98±4.12)%, effect of time: F = 161.552, P = 0.000, effect of intervention: F = 49.224, P = 0.000, interaction effect between intervention and time: F = -4.507, P = 0.000]. The duration of mechanical ventilation and length of ICU stay in the observation group were significantly shorter than those in the control group [duration of mechanical ventilation (hours): 112.68±12.25 vs. 135.32±22.10, length of ICU stay (days): 7.84±1.78 vs. 10.23±2.43, both P < 0.01]. However, there was no significant difference in 24-hour re-intubation rate between the observation group and the control group (0% vs. 2.90%, P > 0.05). CONCLUSIONS: Both early off-bed mobility and progressive early activities can prevent diaphragm weakness in ICU patients undergoing mechanical ventilation, and the effect of early off-bed mobility is better. Early off-bed mobility can significantly shorten the duration of mechanical ventilation and length of ICU stay, and it is safe and feasible.

Application of the whole-course care model (IWF/C Care) for postintensive care syndrome based on an early warning system in critically ill patients: a randomised controlled trial study protocol.

INTRODUCTION: Critically ill patients are at risk of developing postintensive care syndrome (PICS), which is manifested by physical, psychological and cognitive impairment. Currently, there are no programmes that combine early warning systems with interventions for PICS. We hypothesise that a comprehensive care model for PICS based on an early warning system would reduce medical costs and the incidence of PICS. METHODS AND ANALYSIS: The Intensive Care Unit (ICU) -Ward-Family/Community whole-course care (IWF/C Care) trial will be a unicentric, randomised, controlled trial. A total of 138 ICU patients from two ICUs at a university hospital in Guizhou province, China, will be enrolled in February 2023. The inclusion criteria are an age of 18 years or older, an ICU stay of more than 48 hours, provide informed consent and the ability to communicate normally. Patients will be followed for 12 months and randomised in a 1:1:1 ratio to three groups. INTERVENTIONS: Patients in intervention group 1 will be assessed by the PICS early warning system within 24 hours of ICU discharge, and precise interventions will be carried out according to the results; that is, high-risk patients will receive care based on the IWF/C Care model and low-risk patients will receive routine care. All patients in intervention group 2 will receive care based on the IWF/C Care model. The control group will receive routine care. The primary endpoints are the incidence of PICS and quality of life. The secondary endpoints include the incidence of adverse events: the unplanned readmission rate, cost-effectiveness, and the experiences and feelings of patients receiving care based on the IWF/C Care model. The incidence of PICS will be measured at ICU discharge, general ward discharge, the home/community stage and 1 month and 3, 6, 9, and 12 months after discharge. ETHICS AND DISSEMINATION: Ethics approval was obtained from Biomedical Research Ethics Committee of the Affiliated Hospital of Zunyi Medical University (approval number: KLL-2022-780). The results of this study will be distributed through peer-reviewed journals. TRIAL REGISTRATION NUMBER: ChiCTR2300068135.

Automatic Localization of Key Structures for Subthalamic Nucleus-Deep Brain Stimulation Surgery via Prior-Enhanced Multi-Object Magnetic Resonance Imaging Segmentation.

BACKGROUND: Deep brain stimulation (DBS) of the subthalamic nucleus (STN) is an established and effective neurosurgical treatment for relieving motor symptoms in Parkinson disease. The localization of key brain structures is critical to the success of DBS surgery. However, in clinical practice, this process is heavily dependent on the radiologist's experience. METHODS: In this study, we propose an automatic localization method of key structures for STN-DBS surgery via prior-enhanced multi-object magnetic resonance imaging segmentation. We use the U-Net architecture for the multi-object segmentation, including STN, red nucleus, brain sulci, gyri, and ventricles. To address the challenge that only half of the brain sulci and gyri locate in the upper area, potentially causing interference in the lower area, we perform region of interest detection and ensemble joint processing to enhance the segmentation performance of brain sulci and gyri. RESULTS: We evaluate the segmentation accuracy by comparing our method with other state-of-the-art machine learning segmentation methods. The experimental results show that our approach outperforms state-of-the-art methods in terms of segmentation performance. Moreover, our method provides effective visualization of key brain structures from a clinical application perspective and can reduce the segmentation time compared with manual delineation. CONCLUSIONS: Our proposed method uses deep learning to achieve accurate segmentation of the key structures more quickly than and with comparable accuracy to human manual segmentation. Our method has the potential to improve the efficiency of surgical planning for STN-DBS.

Association of Maternal Plasma Manganese with the Risk of Spontaneous Preterm Birth: A Nested Case-Control Study Based on the Beijing Birth Cohort Study (BBCS) in China.

We performed this study to clarify the dynamic changes in maternal manganese (Mn) concentration during pregnancy and its association with spontaneous preterm birth (SPB). A nested case-control study was conducted based on the Beijing Birth Cohort Study (BBCS) from 2018 to 2020. Singleton pregnancy women aged 18-44 (n = 488) were involved in the study, including 244 cases of SPB and 244 controls. All of the participants provided blood samples twice (in their first and third trimesters). Inductively coupled plasma mass spectrometry (ICP-MS) was used for the laboratory analysis, and unconditional logistic regression was used for the statistical analysis. We found that the maternal Mn levels were significantly higher in the third trimester than those in the first trimester (median: 1.23 vs. 0.81 ng/mL). The SPB risk was increased to 1.65 (95% CI: 1.04-2.62, p = 0.035) in the highest Mn level (third tertile) in the third trimester, especially in normal-weight women (OR: 2.07, 95% CI: 1.18-3.61, p = 0.011) or non-premature rupture of membrane (PROM) women (OR: 3.93, 95% CI: 2.00-7.74, p < 0.001). Moreover, a dose-dependent relationship exists between the SPB risk and maternal Mn concentration in non-PROM women (P trend < 0.001). In conclusion, dynamic monitoring of maternal Mn level during pregnancy would be helpful for SPB prevention, especially in normal-weight and non-PROM women.

Semi-supervised medical image segmentation via cross-guidance and feature-level consistency dual regularization schemes.

BACKGROUND: Semi-supervised learning is becoming an effective solution for medical image segmentation because of the lack of a large amount of labeled data. PURPOSE: Consistency-based strategy is widely used in semi-supervised learning. However, it is still a challenging problem because of the coupling of CNN-based isomorphic models. In this study, we propose a new semi-supervised medical image segmentation network (DRS-Net) based on a dual-regularization scheme to address this challenge. METHODS: The proposed model consists of a CNN and a multidecoder hybrid Transformer, which adopts two regularization schemes to extract more generalized representations for unlabeled data. Considering the difference in learning paradigm, we introduce the cross-guidance between CNN and hybrid Transformer, which uses the pseudo label output from one model to supervise the other model better to excavate valid representations from unlabeled data. In addition, we use feature-level consistency regularization to effectively improve the feature extraction performance. We apply different perturbations to the feature maps output from the hybrid Transformer encoder and keep an invariance of the predictions to enhance the encoder's representations. RESULTS: We have extensively evaluated our approach on three typical medical image datasets, including CT slices from Spleen, MRI slices from the Heart, and FM Nuclei. We compare DRS-Net with state-of-the-art methods, and experiment results show that DRS-Net performs better on the Spleen dataset, where the dice similarity coefficient increased by about 3.5%. The experimental results on the Heart and Nuclei datasets show that DRS-Net also improves the segmentation effect of the two datasets. CONCLUSIONS: The proposed DRS-Net enhances the segmentation performance of the datasets with three different medical modalities, where the dual-regularization scheme extracts more generalized representations and solves the overfitting problem.

Dual encoder network with transformer-CNN for multi-organ segmentation.

Medical image segmentation is a critical step in many imaging applications. Automatic segmentation has gained extensive concern using a convolutional neural network (CNN). However, the traditional CNN-based methods fail to extract global and long-range contextual information due to local convolution operation. Transformer overcomes the limitation of CNN-based models. Inspired by the success of transformers in computer vision (CV), many researchers focus on designing the transformer-based U-shaped method in medical image segmentation. The transformer-based approach cannot effectively capture the fine-grained details. This paper proposes a dual encoder network with transformer-CNN for multi-organ segmentation. The new segmentation framework takes full advantage of CNN and transformer to enhance the segmentation accuracy. The Swin-transformer encoder extracts global information, and the CNN encoder captures local information. We introduce fusion modules to fuse convolutional features and the sequence of features from the transformer. Feature fusion is concatenated through the skip connection to smooth the decision boundary effectively. We extensively evaluate our method on the synapse multi-organ CT dataset and the automated cardiac diagnosis challenge (ACDC) dataset. The results demonstrate that the proposed method achieves Dice similarity coefficient (DSC) metrics of 80.68% and 91.12% on the synapse multi-organ CT and ACDC datasets, respectively. We perform the ablation studies on the ACDC dataset, demonstrating the effectiveness of critical components of our method. Our results match the ground-truth boundary more consistently than the existing models. Our approach gains more accurate results on challenging 2D images for multi-organ segmentation. Compared with the state-of-the-art methods, our proposed method achieves superior performance in multi-organ segmentation tasks. Graphical Abstract The key process in medical image segmentation.

TDD-UNet:Transformer with double decoder UNet for COVID-19 lesions segmentation.

The outbreak of new coronary pneumonia has brought severe health risks to the world. Detection of COVID-19 based on the UNet network has attracted widespread attention in medical image segmentation. However, the traditional UNet model is challenging to capture the long-range dependence of the image due to the limitations of the convolution kernel with a fixed receptive field. The Transformer Encoder overcomes the long-range dependence problem. However, the Transformer-based segmentation approach cannot effectively capture the fine-grained details. We propose a transformer with a double decoder UNet for COVID-19 lesions segmentation to address this challenge, TDD-UNet. We introduce the multi-head self-attention of the Transformer to the UNet encoding layer to extract global context information. The dual decoder structure is used to improve the result of foreground segmentation by predicting the background and applying deep supervision. We performed quantitative analysis and comparison for our proposed method on four public datasets with different modalities, including CT and CXR, to demonstrate its effectiveness and generality in segmenting COVID-19 lesions. We also performed ablation studies on the COVID-19-CT-505 dataset to verify the effectiveness of the key components of our proposed model. The proposed TDD-UNet also achieves higher Dice and Jaccard mean scores and the lowest standard deviation compared to competitors. Our proposed method achieves better segmentation results than other state-of-the-art methods.

Characterization of S100A12 from nile tilapia (Oreochromis niloticus) and its roles on inflammatory responses.

S100A12 is a member of S100 proteins family that induces pro-inflammatory response via ligating with the receptor for advanced glycation end products (RAGE) and subsequent activation of intracellular signal transduction pathways. But information about fish S100A12 remain largely unclear. In this study, the S100A12 homolog (On-S100A12) was identified from Nile tilapia (Oreochromis niloticus). On-S100A12 was mainly expressed in liver and intestine. After Streptococcus agalactiae infection in vivo, S100A12 significantly increased in brain, intestine, liver and head kidney, suggesting S100A12 might played roles in immune response. The further in vitro experiments found that recombinant protein of S100A12 (rOn-S100A12) upregulated the expression of IL1-ß, TLR2, TNF-α and inhibited the expression of IL-10, indicating On-S100A12 promoted inflammatory response and activation of M1 macrophages. The present data lay a foundation to further explore the roles of fish S100 during immune defense and will also be beneficial for better understanding of fish immune-regulatory network.

A regularization-driven Mean Teacher model based on semi-supervised learning for medical image segmentation.

Objective.A semi-supervised learning method is an essential tool for applying medical image segmentation. However, the existing semi-supervised learning methods rely heavily on the limited labeled data. The generalization performance of image segmentation is improved to reduce the need for the number of labeled samples and the difficulty of parameter tuning by extending the consistency regularization.Approach.We propose a new regularization-driven Mean Teacher model based on semi-supervised learning for medical image segmentation in this work. We introduce a regularization-driven strategy with virtual adversarial training to improve segmentation performance and the robustness of the Mean Teacher model. We optimize the unsupervised loss function and the regularization term with an entropy minimum to smooth the decision boundary.Main results.We extensively evaluate the proposed method on the International Skin Imaging Cooperation 2017(ISIC2017) and COVID-19 CT segmentation datasets. Our proposed approach gains more accurate results on challenging 2D images for semi-supervised medical image segmentation. Compared with the state-of-the-art methods, the proposed approach has significantly improved and is superior to other semi-supervised segmentation methods.Significance.The proposed approach can be extended to other medical segmentation tasks and can reduce the burden of physicians to some extent.

Preterm delivery rate in China: a systematic review and meta-analysis.

BACKGROUND: Preterm delivery rate is a crucial public health indicator, yet reliable statistic is currently not available in China. In this systematic review and meta-analysis, we aimed to review studies on preterm delivery rate in China, explore sources of heterogeneity, and estimate the preterm delivery rate in China. METHODS: Published studies on preterm delivery rate in China since 2010 were electronically searched from PubMed, Embase, Web of Science, China National Knowledge Infrastructure, China Science and Technology Journal Database, and Wanfang Database, and complemented by manual search. Study selection, data extraction, and quality and bias assessment (using the Joanna Briggs Institute Critical Appraisal Checklist) were conducted by two reviewers independently. Random-effects meta-analysis was performed to estimate the pooled preterm delivery rate, and prespecified stratified analysis was conducted to explore sources of heterogeneity. RESULTS: The database search returned 4494 articles and manual search identified 10 additional studies. In total, 162 studies were eligible, of which 124 were hospital-based and 38 population-based. The pooled preterm delivery rate of hospital-based studies (7.2%; 95% CI: 6.9% to 7.6%) was significantly higher than that of population-based studies (4.9%; 95% CI: 4.5% to 5.4%) (P for subgroup difference < 0.001). Among population-based studies, the rate tended to differ by geography (P for subgroup difference = 0.07): 5.3% for Eastern, 4.6% for Central, and 3.8% for Western. CONCLUSIONS: According to population-based studies, the preterm delivery rate in China is around 5%. This rate is substantially lower than estimates from hospital-based studies or estimates from a combination of both hospital-based and population-based studies as having been done in previous studies.

[Efficacy and safety of conformal thermocoagulation guided by stereotactic electroencephalogram in the treatment of epilepsy caused by focal cortical dysplasia in eloquent cortex].

Objective: To explore the efficacy and safety of stereotactic electroencephalography (SEEG)-guided conformal radiofrequency thermocoagulation for epilepsy caused by focal cortical dysplasia (FCD) in eloquent cortex. Methods: The data of epilepsy patients with conformal thermocoagulation in the Epilepsy Center of Guangdong Sanjiu Brain Hospital from September 2017 to August 2020 were retrospectively analyzed. SEEG electrodes were placed in patients with drug-refractory epilepsy caused by FCD in eloquent cortex with limited boundaries, which was confirmed by preoperative evaluation methods such as imaging and electroencephalography. When designing the electrode placement plan, related software was used to reconstruct the three-dimensional MRI image and lesion. SEEG electrode contacts should be designed to fully cover the lesion as much as possible. After the completion of SEEG monitoring and cortical electrical stimulation, the pre-thermocoagulation and permanent thermocoagulation modes were used in sequence. The mode of direct damage between adjacent contacts of a single electrode and cross-destruction between adjacent contacts of multiple electrodes was combined to ablate the lesions point by point. Results: A total of 22 patients were enrolled, ranging from 2 to 30 years old, with an average age of (15±9) years old. MRI showed that FCD lesions located at pre-central gyrus in 19 cases, at post-central gyrus in 3 cases, at left frontal lobe in 3 cases, at both pre-central and post-central gyrus in 1 case and at both pre-central and left frontal lobe in 2 cases. The length of the lesion was 1.2-4.0 cm, with an average length of (2.2±0.7) cm. Moreover, 7-12 SEEG electrodes were implanted, with an average of (9±2) electrodes. The number of electrodes passing through the lesion was 2-8, with an average of 5±2. The number of thermocoagulation target points was 6 to 83, with an average of 29±18, while the number of target points which proved to have function by cortical simulation was 0-21, with a median of 3.5. The number of direct thermocoagulation target points was 6 to 58, with an average of 23±13, while the number of cross thermocoagulation target points was 0 to 30, with a median of 3. The completion of the whole thermocoagulation was divided into 2 to 5 times. There were 11 cases (50%) who experienced immediate muscle strength decline, 1 case (4.5%) showed slower speech speed during thermocoagulation, 3 cases (13.6%) exhibited muscle strength decline after thermocoagulation, however, only 1 case (4.5%) had permanent hemiparalysis. There were 17 cases of Engel Ⅰ (77.3%), 3 cases of Engel Ⅱ (13.6%), and 2 case of Engel Ⅲ (9.1%), respectively, after follow-up for 6-42 months, with an average of (20±10) months. Conclusion: SEEG-guided conformal radiofrequency thermocoagulation is safe and effective for epilepsy caused by FCD in eloquent cortex with limited boundaries.

Clinical Effects of the COVID-19 Pandemic Among the Uninfected Pregnant Women - 6 PLADs, China, 2019-2020.

SUMMARY: What is already known about this topic? The coronavirus disease 2019 (COVID-19) pandemic potentially affected prenatal care quality and maternal and fetal outcomes globally.What is added by this report? During COVID-19 pandemic period, the rates of caesarean sections (CS) and preterm birth for uninfected pregnant women increased slightly in areas that were relatively severely impacted by the pandemic in China. The overall number of prenatal examinations did not dramatically decrease, while the eligible examinations significantly decreased in Hubei Province.What are the implications for public health practice? Routine prenatal examinations had been well maintained during the pandemic period in China. In the future, in-time prenatal examinations should be provided to improve the quality of screening and management of high-risk pregnancy under pandemic-affected circumstances. Psychological counseling and transfer treatment channels should be strengthened for pregnant women during lockdown period.