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We developed a new preparation to protect probiotic cells from adverse environmental conditions and improve their livability, which is called Lactobacillus casei-Sodium alginate-Chitosan (LSC). The LSC was prepared by mixing probiotics with sodium alginate-chitosan sol. The preparation contained complex calcium ions, which were released in the acidic environment of gastric juice, thus crosslinking to form in-situ gel. Different proportions of sodium alginate-chitosan were prepared to add to simulate gastrointestinal fluid to get the best ratio. The optimal ratio of LSC preparation was compared with traditional gel microspheres to observe the survival effect of probiotics in gastrointestinal fluid environment. Compared with sodium alginate sol, the porosity of sodium alginate-chitosan sol is lower, which is beneficial to the protection of probiotics. When the ratio of chitosan to sodium alginate is 1.5: 1.5 ( w/v ), the protective effect is the best. The protective ability of LSC is 64 times that of traditional microspheres, and it has the potential of synergistic anti-tumor. A probiotic preparation with simple preparation process and better protection effect compared with traditional microspheres was prepared, which has joint anti-tumor potential.

Background The reference values of eNO have certain differences among people of different countries and races. We aimed to obtain the reference value of eNO in healthy children and adolescents (6–18 years old) in China and to explore the associations between the reference values with ages, gender, heights, BMI, and regions. Methods We measured FeNO 50 levels in 5949 healthy Chinese children and adolescents, FeNO 200 and CaNO levels in 658 participants from 16 provinces of 7 administrative areas in China aged 6–18. All persons were studied after obtaining informed consent from children and their parents. Results The mean FeNO 50 of 5949 Chinese children and adolescents aged 6–18 years was 14.1 ppb, with a 95% confidence interval of 1-38.1 ppb. The mean FeNO 200 of 658 persons was 6.9 ppb with a 95% upper confidence interval of 15.0 ppb, and the mean CaNO was 3.0 ppb with a 95% upper confidence interval of 11.2 ppb. In the 6–11 age group, age and height were correlated with the logarithm of FeNO 50 ( P  < 0.001, P  < 0.05). There was no significant correlation between the logarithm of FeNO 200 and gender, age, height and BMI (all P  > 0.05). The logarithm of CaNO was correlated with gender ( P  < 0.05). In the 12–18 age group, gender, height, and region were correlated with the logarithm of FeNO 50 (all P  < 0.001). There was only a weak correlation between the logarithm of FeNO 200 and height ( P  < 0.001). The logarithm of CaNO was negatively correlated with age ( P  < 0.05). Conclusions Higher FeNO 50 , FeNO 200 and CaNO values were found in healthy children and adolescents in China compared with foreign reports, and is affected by age, height, gender, and region. This study provides useful references for clinical application of eNO in children, especially Asian children.

Background Accurate spirometry reference equations are essential for diagnosing and managing respiratory conditions in children. Although the GLI Global Equations have been proposed for general use, there were few Asian populations available for inclusion. This study aims to develop and validate spirometric reference equations for healthy Chinese children. Methods From May 2018 to May 2021, a cross-sectional study involving healthy Chinese Han children aged 4 to 18 years was conducted by 33 research centers across 24 regions in China. Participants were recruited directly from schools, and physical growth indices (height, weight) were measured. Spirometry tests were performed and demographic and medical history data were collected through questionnaires. New prediction equations were developed using multiple linear regression models with age, height, and weight as predictors. And comparisons were made with existing Caucasian and Chinese pediatric reference equations. Results Lung function was assessed in 8929 healthy Chinese Han children. Age, weight, and height emerged as strong predictors of lung function ( p  < 0.001), and sex-specific reference equations incorporating these factors demonstrated high accuracy in internal validation, yielding mean z-scores within a narrow range of -0.004 to -0.069. In comparison, the Zapletal equations overestimated FEV 1 and FEV 1 /FVC while underestimating other lung function parameters. Additionally, the GLI equations underestimated lung function parameters, including FEV 1 , FVC, and FEV 1 /FVC, for both boys and girls. Compared to previous Chinese studies, the z-scores in this study ranged from − 0.97 to 0.93, with some cases showing significant deviations, highlighting the limitations of existing equations. Conclusion This study developed new spirometry reference equations tailored for healthy Chinese children, with differences noted compared to existing equations. These equations reflect contemporary growth patterns and regional diversity in China, providing an additional option for clinical use. Trial registration NO.: ChiCTR: 1,800,019,029. Registered 22 October 2018.

Crimean-Congo hemorrhagic fever virus (CCHFV) is a biosafety level-4 pathogen requiring urgent research and development efforts. The glycoproteins of CCHFV, Gn and Gc, are considered to play multiple roles in the viral life cycle by interactions with host cells; however, these interactions remain largely unclear to date. Here, we analyzed the cellular interactomes of CCHFV glycoproteins and identified 45 host proteins as high-confidence Gn/Gc interactors. These host molecules are involved in multiple cellular biological processes potentially associated with the physiological actions of the viral glycoproteins. Then, we elucidated the role of a representative cellular protein, HAX1. HAX1 interacts with Gn by its C-terminus, while its N-terminal region leads to mitochondrial localization. By the strong interaction, HAX1 sequestrates Gn to mitochondria, thus depriving Gn of its normal Golgi localization that is required for functional glycoprotein-mediated progeny virion packaging. Consistently, the inhibitory activity of HAX1 against viral packaging and hence propagation was further elucidated in the contexts of pseudotyped and authentic CCHFV infections in cellular and animal models. Together, the findings provide a systematic CCHFV Gn/Gc-cell protein-protein interaction map, but also unravel a HAX1/mitochondrion-associated host antiviral mechanism, which may facilitate further studies on CCHFV biology and therapeutic approaches. Here, Ning et al report the cellular interactomes of Crimean-Congo haemorrhagic fever virus glycoproteins and uncover a host restriction factor HAX1 that hijacks the viral glycoproteins to mitochondria, disabling progeny virion packaging.

Abstract Background Patients with polycystic ovary syndrome (PCOS) have a higher risk of obstetric complications. The association between anti-Müllerian hormone (AMH) and gestational hypertension in these patients is poorly understood. Objective To determine the association between serum AMH levels and gestational hypertension in patients with PCOS undergoing fresh embryo transfer. Methods This retrospective study included 649 patients with PCOS who had singleton live births after undergoing fresh embryo transfers. The association of AMH with gestational hypertension in these patients was estimated before and after propensity score matching. Results Patients with gestational hypertension had higher AMH levels than those without gestational hypertension. In single-factor logistic regression, the odds of gestational hypertension increased by 11.7% and 18.6% for every 1ng/mL increase in AMH before and after adjusting for confounding factors (odds ratio [OR], 1.117; 95% CI, 1.025-1.217; P = .012; adjusted OR, 1.186; 95% CI, 1.061-1.327; adjusted P = .003), respectively. The odds of gestational hypertension increased more than 100% (adjusted OR, 2.635; 95% CI, 1.132-6.137; adjusted P = .025) in the 75th percentile group (>9.30 ng/mL) and more than 3 times (adjusted OR, 4.75; 95% CI, 1.672-13.495; adjusted P = .003) in the 90th percentile group (>12.31 ng/mL) compared to the without gestational hypertension group. AMH level was still associated with gestational hypertension after propensity score matching. The area under the curve of AMH predicting gestational hypertension was 0.654 (95% CI, 0.532-0.776; P = .011) with an optimal cutoff value of 11.975 ng/mL. Conclusion High serum AMH level prepregnancy (especially at levels >9.30 ng/mL) indicates a high odds of gestational hypertension in patients with PCOS undergoing fresh embryo transfer.

In order to compare and analyze the positioning efficiency of the magnetic tensor location method, this paper studies the blind spots of the magnetic tensor location method. By constructing two magnetic tensor localization models, the localization principles of the single-point magnetic tensor localization method (STLM) and the two-point magnetic tensor linear localization method (TTLM) are analyzed. Furthermore, the eigenvalue analysis method is studied to analyze the blind spots of STLM, and the spherical analysis method is proposed to analyze the blind spots of TTLM. The results show that when the direction of any measuring point is perpendicular to the direction of the target magnetic moment, blind spots of STLM appear. However, TTLM still has good positioning performance in the blind spot.

As a kind of industrial solid waste, lead–zinc waste slag can easily cause heavy metal migration in acid environments, resulting in safety risks. Along these lines, in this work, the waste slag of a lead–zinc mining area in western Qinling, Shaanxi, China, was selected as the experimental material. Seven groups of acid soaking solutions with different pH values were set up with three parallel samples in each group, and the acid soaking experiments were conducted for 100 days. During the experiment, the electrical conductivity, pH value, and heavy metal content of the solution, as well as the pore distribution and heavy metal content of the waste slag surface, were measured. The results showed that with pH = 4 and pH = 7 as the environmental limit values, the pH value, electrical conductivity (EC), and heavy metal contents in the solution changed to different types after the waste slag was soaked in the solution with a pH of less than 4 and the solution with a pH of 5–7. The release of heavy metals from waste slag exceeded the discharge standard in the environment with a pH of less than 4, and the pore structure of waste slag was obviously enhanced, especially in the soaking solution with an initial pH of 1. The maximum soaking amounts of Zn, Pb, and Cd were 2.584 mg/L, 1.28 mg/L, and 0.0169 mg/L, respectively, during the experiment, which did not meet the “Environmental quality standards for surface water” (GB 3838-2002) and could not be excreted as direct surface water. However, when the environmental pH was greater than 7, the heavy metals showed reverse adsorption. This result indicated that when the acid soaking solution entered the alkaline range, the heavy metal content in the solution was less, which can basically meet the discharge standard. However, the pores of waste slag continued to expand. Our work provides valuable insights into the treatment of waste slag and environmental protection in lead-zinc mining areas containing sulfur.

Objectives To develop a deep learning-based automatic segmentation method for cortex and marrow in mandibular condyle on cone-beam computed tomography (CBCT) images and explore its clinical application. Methods 825 condyles of 490 CBCT images from 3 centers of Stomatology hospital affliated to Zhejiang University School of Medicine were collected. A deep learning model was developed for simultaneous segmentation of cortex and marrow in mandibular condyle. It included a region of interest extraction network and a segmentation network based on 3D U-net, with modifications made to improve the segmentation boundaries. To evaluate its clinical potential, the model's segmentation efficiency and accuracy were compared with those of both junior and senior oral and maxillofacial radiologists. Additionally, the model's ability to assist junior radiologists in diagnosis through visualization and quantitative analysis of the generated 3D model was also assessed. Results The Dice similarity coefficient of the deep learning model was 0.901 (cortex), 0.969 (marrow), and 0.982 (entire condyle). Hausdorff distance was 0.755 mm (cortex), 0.826 mm (marrow), and 0.760 mm (entire condyle). The model outperformed radiologists across all segmentation metrics, completing the task in merely 15.06 s. With the assistance of visualization and quantitative analysis generated from the model’s segmentation, the diagnostic accuracy of junior radiologists significantly improved. Conclusions The proposed deep learning-based model achieved accurate and efficient segmentation for mandibular condylar cortex and marrow. It possessed capability to generate precise 3D models, facilitating visual quantitative measurement and aiding in the diagnosis of condylar bony changes. This model holds potential for clinical applications in orthognathic surgery, orthodontic treatment, and other TMJ-related interventions.

The SMILE ground segment comprises the Chinese Academy of Sciences (CAS) ground segment and the European Space Agency (ESA) ground segment, which collaborate closely on this mission. The Ground Support System (GSS) and the Science and Application System (SAS) are two important components of the CAS ground segment. Development of these systems began in 2016, focusing on requirements for addressing the significant challenges associated with the SMILE mission. The GSS is primarily responsible for data reception, mission operations, data processing, data management, and data services. It has established an operational platform based on a “common platform + mission-specific plug-ins” model, enabling support for the SMILE mission through the development of tailored plugins. The SAS functions as a dedicated scientific research center for the SMILE mission within CAS, managing science operations, processing scientific data, and conducting scientific data analysis. Its establishment was driven by the unique requirements of the SMILE mission. Additionally, the SAS is tasked with fostering collaboration between CAS and ESA, designing effective frameworks to coordinate scientists in planning SMILE science operations. This paper provides a brief overview of the design of the GSS and SAS, as well as SMILE mission operations. We anticipate that these two systems will effectively support the SMILE mission in the future.