Streptomyces chengbuensis sp. nov., isolated from the rhizosphere soil of Cathaya argyrophylla.

Strain HUAS CB01T was a novel actinobacterium which was isolated from the rhizosphere soil of Cathaya argyrophylla, Chengbu Miao Autonomous County of Hunan Province, China. The strain formed well-growing substrate mycelium, diffusible pigments, and aerial mycelium, and differentiated into spiral-type spore chains composed of smooth-surface rod-shaped spores. Phylogenetic analysis on account of 16 S rRNA gene sequence demonstrated the strain HUAS CB01T was a member of the genus Streptomyces and had a close relationship with Streptomyces wuyuanensis CGMCC 4.7042 T (100%) and Streptomyces marianii ICN19T (99.86%). Genome-based comparisons indicated that strain HUAS CB01T could be distinctly different from its closest species, Streptomyces wuyuanensis CGMCC 4.7042 T, Streptomyces marianii ICN19T, with ANIm and dDDH results of 92.78% and 45.90%, 92.22% and 43.30%, respectively, far less than 96.7 and 70% cut-off points recommended for delineating species. The main cellular fatty acids concluded anteiso-C15:0, iso-C14:0, iso-C16:0, C16:0 and C16:1 2OH. The menaquinones were MK-9(H4), MK-9(H6) and MK-9(H8) and the whole-cell sugars consisted of ribose and mannose. The polar lipids included phosphatidyl ethanolamine, diphosphatidylglycerol, phosphatidylglycerol, mannosides and unidentified phospholipids. According to these genotypic and phenotypic characteristics, strain HUAS CB01T can be distinguished and representative to be a novel species of the genus Streptomyces, for which the name Streptomyces chengbuensis is proposed. The type strain is HUAS CB01T ( = MCCC 1K08666T = JCM 36277 T).

Kitasatospora cathayae sp. nov., a novel endophytic actinomycete isolated from the leaves of Cathaya argyrophylla.

Strain HUAS 3-15T was isolated from the leaves of Cathaya argyrophylla collected from Chenzhou, Hunan Province, PR China. The main fatty acids (>5.0 %) of the strain were anteiso-C15 : 0, C16 : 0, C18 : 1 ω9c, iso-C16 : 0, summed feature 5 (C18 : 2 ω6,9c/C18 : 0 ante), iso-C15 : 0 and anteiso-C17 : 0. MK-9(H6), MK-9(H8) and MK-9(H4) were detected as respiratory quinones. The diagnostic cell-wall diamino acid was meso-diaminopimelic acid. Galactose, glucose and ribose were also present in the cell wall. The major polar lipids consisted of diphosphatidylglycerol, phosphatidyl ethanolamine, phosphatidylinositol mannosides and unidentified phospholipids. The DNA G+C content of the genome sequence, consisting of 8 860 963 bp, is 72.4 mol%. blast analysis based on 16S rRNA gene sequences revealed that the strain belongs to the genus Kitasatospora, with 99.37, 99.03, 98.95, 98.68 and 98.67 % sequence similarity to Kitasatospora aureofaciens ATCC 10762T, Kitasatospora viridis DSM 44826T, Kitasatospora xanthocidica NBRC 13469T, Kitasatospora aburaviensis NRRL B-2218T and Kitasatospora kifunensis IFO 15206T, respectively. Phylogenetic trees based on 16S rRNA gene and whole-genome sequences demonstrated that strain HUAS 3-15T formed a well-supported cluster with K. aureofaciens ATCC 10762T. Further genomic characterization through average nucleotide identity (ANIb/m) and digital DNA-DNA hybridization analysis between strain HUAS 3-15T and K. aureofaciens ATCC 10762T showed values of 90.62/92.55 % and 45.3 %, respectively, lower than the 95-96 % ANI threshold and 70.0 % cutoff used as guideline values for species delineation in bacteria. Furthermore, the differences between the strain and its phylogenomic neighbour in terms of physiological (e.g. sole carbon source growth) and chemotaxonomic (e.g. cellular fatty composition) characteristics further supported this conclusion. Consequently, we concluded that strain HUAS 3-15T represents a novel species of the genus Kitasatospora, for which the name Kitasatospora cathayae sp. nov. is proposed. The type strain is HUAS 3-15T (=MCCC 1K08542T=JCM 36274T).

Adaptable cascaded registration for personalized maxilla completion and cleft defect volume estimation.

BACKGROUND: Cone-beam computed tomography (CBCT) images provide high-resolution insights into the underlying craniofacial anomaly in patients with cleft lip and palate (CLP), requiring non-negligible annotation costs to measure the cleft defect for the guidance of the clinical secondary alveolar bone graft procedures. Considering the cumbersome volumetric image acquisition, there is a lack of paired CLP CBCTs and normal CBCTs for learning-based anatomical structure restoration models. Nowadays, the registration-based method relieves the annotation burden, though one-shot registration and the regular mask are limited to handling fine-grained shape variations and harmony between restored bony tissues and the defected maxilla. PURPOSE: This study aimed to design and evaluate a novel method for deformable partial registration of the CLP CBCTs and normal CBCTs, enabling personalized maxilla completion and cleft defect volume prediction from CLP CBCTs. METHODS: We proposed an adaptable deep registration framework for personalized maxilla completion and cleft defect volume prediction from CLP CBCTs. The key ingredient was a cascaded partial registration to exploit the maxillary morphology prior and attribute transfer. Cascaded registration with coarse-to-fine registration fields handled morphological variations of cleft defects and fine-grained maxillary restoration. We designed an adaptable cleft defect mask and volumetric Boolean operators for reliable voxel filling of the defected maxilla. A total of 36 clinically obtained CLP CBCTs were used to train and validate the proposed model, among which 22 CLP CBCTs were used to generate a training dataset with 440 synthetic CBCTs by B-spline deformation-based data augmentation and the remaining for testing. The proposed model was evaluated on maxilla completion and cleft defect volume prediction from clinically obtained unilateral and bilateral CLP CBCTs. RESULTS: Extensive experiments demonstrated the effectiveness of the adaptable cleft defect mask and the cascaded partial registration on maxilla completion and cleft defect volume prediction. The proposed method achieved state-of-the-art performances with the Dice similarity coefficient of 0.90 ± $\pm$ 0.02 on the restored maxilla and 0.84 ± $\pm$ 0.04 on the estimated cleft defect, respectively. The average Hausdorff distance between the estimated cleft defect and the manually annotated ground truth was 0.30 ± $\pm$ 0.08 mm. The relative volume error of the cleft defect was 0.09 ± $0.09\pm$ 0.08. The proposed model allowed for the prediction of cleft defect maps that were in line with the ground truth in the challenging unilateral and bilateral CLP CBCTs. CONCLUSIONS: The results suggest that the proposed adaptable deep registration model enables patient-specific maxilla completion and automatic annotation of cleft defects, relieving tedious voxel-wise annotation and image acquisition burdens.

Circ_0082374 Promotes the Tumorigenesis and Suppresses Ferroptosis in Non-small Cell Lung Cancer by Up-Regulating GPX4 Through Sequestering miR-491-5p.

Circular RNAs (circRNAs) have been identified to be dysregulated in non-small cell lung cancer (NSCLC) and implicated in the progression of this cancer. Here, this work aimed to investigate the role and mechanism of circ_0082374 on NSCLC progression. Levels of circ_0082374, miR-491-5p, GPX4 (glutathione peroxidase 4) and epithelial-mesenchymal transition (EMT)-related proteins were examined by quantitative real-time PCR or western blotting, respectively. Cell proliferation and metastasis were detected using cell counting kit-8, colony formation, EdU, transwell, and Scratch assays. Cell ferroptosis was evaluated by measuring cell survival after the treatment of different ferroptosis inducers or inhibitors, as well as the accumulation of intracellular reactive oxygen species (ROS), ferrous iron (Fe2+) and malondialdehyde (MDA). The binding between miR-491-5p and circ_0082374 or GPX4 was confirmed using dual-luciferase reporter and RNA pull-down assays. In vivo experiments were conducted using murine xenograft assay and immunohistochemistry. Circ_0082374 was a stable circRNA with high expression in NSCLC tissues and cells. Functionally, circ_0082374 silencing suppressed NSCLC cell proliferation and metastasis. Moreover, its down-regulation enhanced ferroptosis by decreasing iron and lipid peroxidation accumulation. Mechanistically, circ_0082374 could indirectly up-regulate GPX4 expression via miR-491-5p, indicating the circ_0082374/miR-491-5p/GPX4 competitive endogenous RNAs (ceRNA) network. Rescue experiments demonstrated that the miR-491-5p/GPX4 axis mediated the regulatory effects of circ_0082374 exerted on NSCLC cells. Moreover, knockdown of circ_0082374 impeded NSCLC growth and EMT via regulating miR-491-5p and GPX4. Circ_0082374 silencing could suppress NSCLC cell proliferation, metastasis and induce ferroptosis through miR-491-5p/GPX4 axis, suggesting a novel therapeutic approach for NSCLC patients.

Detecting Gene-Gene Interaction among DNA Repair Genes in Chinese non-Syndromic Cleft lip with or Without Palate Trios.

OBJECTIVE: The objective of this study is to investigate the gene-gene interactions associated with NSCL/P among DNA repair genes. DESIGN: This study included 806 NSCL/P case-parent trios from China. Quality control process was conducted for genotyped single nucleotide polymorphisms (SNPs) located in six DNA repair genes (ATR, ERCC4, RFC1, TYMS, XRCC1 and XRCC3). We tested gene-gene interactions with Cordell's method using statistical package TRIO in R software. Bonferroni corrected significance level was set as P = 4.24 × 10-4. We also test the robustness of the interactions by permutation tests. SETTING: Not applicable. PATIENTS/PARTICIPANTS: A total of 806 NSCL/P case-parent trios (complete trios: 682, incomplete trios: 124) with Chinese ancestry. INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURE(S): Not applicable. RESULTS: A total of 118 SNPs were extracted for the interaction tests. Fourteen pairs of significant interactions were identified after Bonferroni correction, which were confirmed in permutation tests. Twelve pairs were between ATR and ERCC4 or XRCC3. The most significant interaction occurred between rs2244500 in TYMS and rs3213403 in XRCC1(P = 8.16 × 10-15). CONCLUSIONS: The current study identified gene-gene interactions among DNA repair genes in 806 Chinese NSCL/P trios, providing additional evidence for the complicated genetic structure underlying NSCL/P. ATR, ERCC4, XRCC3, TYMS and RFC1 were suggested to be possible candidate genes for NSCL/P.

Failure to thrive in pediatric patients with congenital heart disease: a cross-sectional study of 13,256 patients.

Background: The prevalence and risk factors for failure to thrive (FTT) in pediatric patients with congenital heart disease (CHD) remain ambiguous. We aimed to investigate the prevalence, growth profiles, risk factors, and vulnerable subtypes of CHD associated with FTT in pediatric patients with CHD. Methods: This was a cross-sectional study based on Chinese Database for Congenital Heart Surgery. FTT was defined as either stunting or underweight (height or weight standard deviation score <-2), and they were standardized by references of normal Chinese population. Risk factors was determined with logistic regression model, and growth profiles were delineated in each subgroup. Findings: A total of 13,256 CHD patients were included in this study, with 3994 patients of mild CHD, 7195 patients of moderate CHD and 2067 patients of complex CHD. The prevalence of stunting, underweight and FTT was 24%, 29.3% and 36.9%, respectively. Preoperative anaemia, left ventricle systolic dysfunction, younger age, more complex CHD types, lower birth weight and genetic syndrome were found to be the risk factors for FTT in CHD patients. Interrupted aortic arch was revealed to be the most severe group associated with FTT. Interpretation: FTT is ubiquitous in patients with CHD and exacerbated in high-risk subgroups. Our findings hinted the necessity of early identification and intervention for FTT in patients with CHD during daily practice of pediatrics, as it has the potential to improve outcomes and enhance their quality of life. Furthermore, we advocate for the initiation of prospective research with longitudinal data to comprehensively investigate the association between FTT and CHD across the lifespan. Funding: This study was supported by National High Level Hospital Research Funding (2022-GSP-GG-19), Capital Health Research and Development of Special Fund (2022-1-4032) and National Key R&D Program of China (2022YFC3600202 and 2022YFC3600203).

Brain white matter alterations in young adult male patients with childhood-onset growth hormone deficiency: a diffusion tensor imaging study.

PURPOSE: This study aimed to detect white matter changes and different effects of thyroid hormone on the white matter integrity in young adult male patients with childhood-onset growth hormone deficiency (CO-GHD), compared with healthy people. METHODS: Magnetic resonance imaging (structural imaging and diffusion tensor imaging) was performed in 17 young adult male patients with CO-GHD and 17 healthy male controls. The white matter volume, mean diffusivity (MD) values and fractional anisotropy (FA) values were quantified and compared between two groups (CO-GHD group vs. control group). We assessed the interaction effects between thyroid hormone and groups (CO-GHD group vs. control group) on white matter integrity. RESULTS: Patients with CO-GHD exhibited similar white matter volumes compared with controls. However, compared with the controls, patients with CO-GHD showed a significant reduction in FA values in six clusters and a substantial increase in MD values in four clusters, mainly involving the corticospinal tracts, corpus callosum and so on. Moreover, after correcting for insulin-like growth factor-1 levels, the significant interaction effects between groups (CO-GHD group vs. control group) and serum free thyroxine levels on MD values were noted in three clusters, mainly involving in superior longitudinal fasciculus and sagittal stratum. CONCLUSION: In conclusion, young males with CO-GHD showed white matter changes in multiple brain regions and different effects of thyroid hormone on the white matter integrity.

Magnetic resonance imaging of knees: a novel approach to predict recombinant human growth hormone therapy response in short-stature children in late puberty.

BACKGROUND: There is no appropriate tool to predict recombinant human growth hormone (rhGH) response before therapy initiation in short-stature children in late puberty. The current study aimed to explore the associations between magnetic resonance imaging (MRI) stages of the knee growth plates and rhGH response in short-stature children in late puberty. METHODS: In this prospective cohort study, short-stature children in late puberty were treated with rhGH and followed up for 6 months. We proposed a novel knee MRI staging system according to the growth plate states of distal femurs or proximal tibias and divided the participants into three groups: unclosed growth plate group, marginally closed growth plate group, and nearly closed growth plate group. The primary outcomes were height gain and growth velocity (GV), which were assessed three months later. RESULTS: Fifty participants were enrolled, including 23 boys and 27 girls. GV and height gain after 6 months of rhGH therapy decreased successively in the three groups with an increased degree of growth plate fusion, especially when grouped by proximal tibias (GV1-3 mon from 9.38 to 6.08 to 4.56 cm/year, GV4-6 mon from 6.75 to 4.92 to 3.25 cm/year, and height gain from 4.03 to 2.75 to 1.95 cm, all P < 0.001). Moreover, the MRI stages of growth plates independently served as a significant variable for GV and height gain after therapy, especially when grouped by proximal tibias (all P < 0.01). CONCLUSION: The MRI staging method is expected to be an effective tool for predicting rhGH response before therapy initiation in short-stature children in late puberty.

Evaluation of growth status of children with non-syndromic oral clefts.

To assess the growth status of children with non-syndromic oral clefts (NSOC) and explore potential influencing factors. The data of NSOC children aged ≤5 years hospitalized between December 2018 and June 2020 were retrieved and evaluated, including their height, weight, NSOC subtypes and demographic characteristics before reparative surgeries. The growth status of the children was assessed using height-for-age Z-score (HAZ), weight-for-age Z-score (WAZ) and weight-for-height Z-score (WHZ). In total, 504 NSOC children (271 females & 233 males) were included. The proportion of stunting (HAZ <-2), underweight (WAZ <-2) and wasting (WHZ <-2) was 4.96%, 5.16% and 3.97%, respectively. In addition, we observed that HAZ and WAZ decreased with increasing age (both p < 0.01). Moreover, non-syndromic cleft palate only (NSCP) and non-syndromic cleft lip and palate (NSCLP) were associated with lower HAZ and WAZ compared with non-syndromic cleft lip only (NSCL) (all p < 0.01), while NSCLP was associated with a lower WHZ compared with NSCL (p < 0.01). The growth retardation and low weight rate of NSOC children under 5 years old were higher than the national average level and differed by the age of NSOC children and disease subtypes. Further improvements are warranted to promote the growth status of the NSOC-affected children.

Safflower yellow and its main component hydroxysafflor yellow A alleviate hyperleptinemia in diet-induced obesity mice through a dual inhibition of the GIP-GIPR signaling axis.

Glucose-dependent insulinotropic polypeptide (GIP) is a gastrointestinal hormone secreted by K cells in the small intestine and is considered an obesity-promoting factor. In this study, we systematically investigated the anti-obesity effects of intragastric safflower yellow (SY)/hydroxysafflor yellow A (HSYA) and the underlying mechanism for the first time. Our results showed that intragastric SY/HSYA, rather than an intraperitoneal injection, notably decreased serum GIP levels and GIP staining in the small intestine in diet-induced obese (DIO) mice. Moreover, intragastric SY/HSYA was also first found to significantly suppress GIP receptor (GIPR) signaling in both the hypothalamus and subcutaneous White adipose tissue. Our study is the first to show that intragastric SY/HSYA obviously reduced food intake and body weight gain in leptin sensitivity experiments and decreased serum leptin levels in DIO mice. Further experiments demonstrated that SY treatment also significantly reduced leptin levels, whereas the inhibitory effect of SY on leptin levels was reversed by activating GIPR in 3 T3-L1 adipocytes. In addition, intragastric SY/HSYA had already significantly reduced serum GIP levels and GIPR expression before the serum leptin levels were notably changed in high-fat-diet-fed mice. These findings suggested that intragastric SY/HSYA may alleviate diet-induced obesity in mice by ameliorating hyperleptinemia via dual inhibition of the GIP-GIPR axis.

Machine learning in 3D auto-filling alveolar cleft of CT images to assess the influence of alveolar bone grafting on the development of maxilla.

BACKGROUND: Machine learning based auto-segmentation of 3D images has been developed rapidly in recent years. However, the application of this new method in the research of patients with unilateral cleft lip and palate (UCLP) is very limited. In this study, a machine learning algorithm utilizing 3D U-net was used to automatically segment the maxilla, fill the cleft and evaluate the alveolar bone graft in UCLP patients. Cleft related factors and the surgery impact on the development of maxilla were analyzed. METHODS: Preoperative and postoperative computed tomography images of 32 patients (64 images) were obtained. The deep-learning-based protocol was used to segment the maxilla and defect, followed by manual refinement. Paired t-tests and Mann-Whitney tests were performed to reveal the changes of the maxilla after surgery. Two-factor, two-level analysis for repeated measurement was used to examine the different trends of growth on the cleft and non-cleft sides of the maxilla. Pearson and Spearman correlations were used to explore the relationship between the defect and the changes of the maxillary cleft side. RESULTS: One-year after the alveolar bone grafting surgery, different growth amount was found on the cleft and non-cleft sides of maxilla. The maxillary length (from 34.64 ± 2.48 to 35.67 ± 2.45 mm) and the alveolar length (from 36.58 ± 3.21 to 37.63 ± 2.94 mm) increased significantly only on the cleft side while the maxillary anterior width (from 11.61 ± 1.61 to 12.01 ± 1.41 mm) and posterior width (from 29.63 ± 2.25 to 30.74 ± 2.63 mm) increased significantly only on the non-cleft side after surgery. Morphology of the cleft was found to be related to the pre-surgical maxillary dimension on the cleft side, while its correlation with the change of the maxilla after surgery was low or not statistically significant. CONCLUSION: The auto-segmentation of the maxilla and the cleft could be performed very efficiently and accurately with the machine learning method. Asymmetric growth was found on the cleft and non-cleft sides of the maxilla after alveolar bone graft in UCLP patients. The morphology of the cleft mainly contributed to the pre-operation variance of the maxilla but had little impact on the maxilla growth after surgery.

Reward-Adaptive Reinforcement Learning: Dynamic Policy Gradient Optimization for Bipedal Locomotion.

Controlling a non-statically bipedal robot is challenging due to the complex dynamics and multi-criterion optimization involved. Recent works have demonstrated the effectiveness of deep reinforcement learning (DRL) for simulation and physical robots. In these methods, the rewards from different criteria are normally summed to learn a scalar function. However, a scalar is less informative and may be insufficient to derive effective information for each reward channel from the complex hybrid rewards. In this work, we propose a novel reward-adaptive reinforcement learning method for biped locomotion, allowing the control policy to be simultaneously optimized by multiple criteria using a dynamic mechanism. The proposed method applies a multi-head critic to learn a separate value function for each reward component, leading to hybrid policy gradients. We further propose dynamic weight, allowing each component to optimize the policy with different priorities. This hybrid and dynamic policy gradient (HDPG) design makes the agent learn more efficiently. We show that the proposed method outperforms summed-up-reward approaches and is able to transfer to physical robots. The MuJoCo results further demonstrate the effectiveness and generalization of HDPG.

Evidence of the folate-mediated one-carbon metabolism pathway genes in controlling the non-syndromic oral clefts risks.

The folate-mediated one-carbon metabolism pathway is thought to play an important role in the etiology of non-syndromic oral clefts (NSOFC), although none of the genes in this pathway has shown significant signals in genome-wide association studies (GWAS). Recent evidence indicated that enhanced understanding could be gained by aggregating multiple SNPs effect simultaneously into polygenic risk score (PRS) to assess its association with disease risks. This study is aimed to assess the association between the genetic effect of folate-mediated one-carbon metabolism pathway and NSOFC risks using PRS based on a case-parent trio design. A total of 297 SNPs mapped from 18 genes in the folate-mediated one-carbon metabolism pathway were aggregated from a GWAS of 2458 case-parent trios recruited from an international consortium. We found a PRS based on the folate-mediated one-carbon metabolism pathway was significant among all NSOFC trios (OR = 1.95, 95% CI: 1.66-2.28, p = 2.39 × 10-16 ), as well as two major subtypes, non-syndromic cleft lip with or without cleft palate (NSCL/P) trios (OR = 1.71, 95% CI: 1.50-1.96, p = 7.66 × 10-15 ) and non-syndromic cleft palate only (NSCPO) trios (OR = 1.51, 95% CI: 1.36-1.68, p = 2.1 × 10-14 ). Similar results were also observed in further subgroup analyses stratified into Asian and European trios. The averaged PRS of the folate-mediated one-carbon metabolism pathway varied between the NSOFC case group and its comparison group (p < 0.05) with higher average PRS in the cases. Moreover, the top 5% pathway PRS group had 2.25 (95% CI: 1.85-2.73) times increased NSOFC risk, also 3.09 (95% CI: 2.50-3.81) and 2.06 (95% CI: 1.39-3.02) times increased risk of NSCL/P and NSCPO compared to the remainder of the distribution. The results of our study confirmed the folate-mediated one-carbon metabolism pathway was important in controlling risk to NSOFC and this study enhanced evidence towards understanding the genetic risks of NSOFC.

Distinct community assembly and co-existence of arbuscular mycorrhizal fungi and diazotrophs across large-scale soil fertility to improve functions in alfalfa cultivation systems.

Unravelling the community assembly processes of arbuscular mycorrhizal fungi (AMF) and diazotrophs as well as their co-existence under different soil fertility environments are vital to develop a better understanding of agroecosystem functions, which is a crucial yet poorly understood topic. We examined the soils from 99 typical alfalfa cultivation systems to formulate a comprehensive picture of AMF and diazotrophic community and presented the first simultaneous investigation of the assembly processes and their co-existence. The distributions of both AMF and diazotrophic communities were significantly (p < 0.05) corresponded to soil integrated fertility index (IFI). We quantified the relative contributions of five ecological processes in AMF and diazotrophic community assembly under different soil fertility environments, with stochastic assembly primarily determined across all soil fertility groups. The coexistence networks of AMF and diazotrophs were also notably different among typical soil fertility systems, where the most complex interactions were observed in high fertility system while medium fertility system was found to be the simplest. The active hubs detected in different fertility system were sensitively responded to different soil variables. We offered new opportunities to improve agroecosystem functions, especially for legumes, by regulating the potential key species or indirectly manipulating their drivers.

Predictive models for small-for-gestational-age births in women exposed to pesticides before pregnancy based on multiple machine learning algorithms.

Background: The association between prenatal pesticide exposures and a higher incidence of small-for-gestational-age (SGA) births has been reported. No prediction model has been developed for SGA neonates in pregnant women exposed to pesticides prior to pregnancy. Methods: A retrospective cohort study was conducted using information from the National Free Preconception Health Examination Project between 2010 and 2012. A development set (n = 606) and a validation set (n = 151) of the dataset were split at random. Traditional logistic regression (LR) method and six machine learning classifiers were used to develop prediction models for SGA neonates. The Shapley Additive Explanation (SHAP) model was applied to determine the most influential variables that contributed to the outcome of the prediction. Results: 757 neonates in total were analyzed. SGA occurred in 12.9% (n = 98) of cases overall. With an area under the receiver-operating-characteristic curve (AUC) of 0.855 [95% confidence interval (CI): 0.752-0.959], the model based on category boosting (CatBoost) algorithm obtained the best performance in the validation set. With the exception of the LR model (AUC: 0.691, 95% CI: 0.554-0.828), all models had good AUCs. Using recursive feature elimination (RFE) approach to perform the feature selection, we included 15 variables in the final model based on CatBoost classifier, achieving the AUC of 0.811 (95% CI: 0.675-0.947). Conclusions: Machine learning algorithms can develop satisfactory tools for SGA prediction in mothers exposed to pesticides prior to pregnancy, which might become a tool to predict SGA neonates in the high-risk population.

Cognitive bias toward the Internet: The causes of adolescents' Internet addiction under parents' self-affirmation consciousness.

The Internet plays a crucial part in the adolescent life. However, as a product of modernization, the Internet has brought a lifestyle different from that of our parents who tend to regard excessive exposure to the Internet as a manifestation of the adolescent Internet addiction. The cognitive bias against the Internet seem to have been arisen among the parents. Under the theoretical framework of self-efficacy and empathy, this study adopts PLS-SEM to analyze the contributing factors of the adolescent Internet addiction from the perspective of self-affirmation consciousness of parents. The result demonstrates that self-affirmation consciousness has a significant positive effect on the empathy process; the empathy process and self-affirmation have a significant positive effect on cognitive bias; and the empathy process acts as a mediator between self-affirmation and cognitive bias. To sum up, through the investigation of the causes of adolescent Internet addiction, this study explores the formation process of parents' cognitive bias toward the Internet under the influence of self-affirmation consciousness, verifying the practical effects of empathy in the process of promoting rational thinking of parents toward the Internet and adolescent Internet use, and at the same time promoting the harmonious development of parent-child relationships to a certain extent.

Reduced Bone Mineral Density in Middle-Aged Male Patients with Adult Growth Hormone Deficiency.

The aim of the work was to investigate the bone mineral density (BMD) in middle-aged male patients with both childhood-onset (CO) and adulthood-onset (AO) adult growth hormone deficiency (AGHD). In this retrospective cross-sectional study in a major medical center in China, dual X-ray absorptiometry was performed in 50 male AGHD patients (average age was 35.2±9.8 years) and 50 age- and BMI-matched non-athletic healthy men. BMD was compared between AGHD patients and controls. Compared with healthy controls, AGHD group had significantly decreased IGF-1 (p1<0.001) and IGF-1 SDS (p1<0.001). Serum testosterone levels were significantly lower in AGHD patients (p1<0.001), mainly in AO AGHD patients (p3<0.001). The BMD of the femoral neck, trochanter, femoral shaft, total hip, and lumbar spine were significantly lower in all AGHD patients compared with healthy controls (all p1<0.05), especially in CO AGHD patients (all p2<0.05). Multiple stepwise linear regression indicated AGHD was negatively correlated with BMD at each site (ß<0, p<0.05). Additionally, serum testosterone level was an independent influencing factor of BMD of the femoral neck (ß=0.256, p=0.018) and lumbar spine (ß=0.219, p=0.040). BMD was significantly reduced in AGHD patients, especially in CO AGHD patients. Our data suggested that the status of growth hormone deficiency and testosterone level were important for maintaining of bone mineral density in middle-aged male patients with AGHD.

The Antiobesity Effect and Safety of GLP-1 Receptor Agonist in Overweight/Obese Patients Without Diabetes: A Systematic Review and Meta-Analysis.

Aim To determine the antiobesity effect and safety of glucagon-like peptide-1 receptor agonist (GLP-1RA) including liraglutide, exenatide and semaglutide treatment in overweight/obese patients without diabetes. The random-effect model was used to pool data extracted from included literatures. The weighted mean difference (WMD), odds ratio and 95% confidence interval (CI) were used to present the meta-analysis results (PROSPERO registration number: CRD 42020173199). The sources of intertrial heterogeneity, bias and the robustness of results were evaluated by subgroup analysis, sensitivity analysis and regression analysis, respectively. A total of 24 RCTs were recruited in the present analysis which included 5867 patients. The results showed that the treatment of overweight/obese patients without diabetes with GLP-1RAs including liraglutide, exenatide and semaglutide significantly achieved greater weight loss than placebo [WMD=-5.39, 95% CI (-6.82, -3.96)] and metformin [WMD=-5.46, 95% CI (-5.87, -5.05)]. The subgroup analysis showed that semaglutide displayed the most obvious antiobesity effect in terms of weight loss, the reduction of body mass index (BMI) and waist circumference (WC). However, GLP-1RAs treatments had more gastrointestinal adverse events (such as nausea and vomiting) than placebo and Met. The subgroup analysis also represented that semaglutide displayed the lowest risk of gastrointestinal adverse events among three kinds of GLP-1RAs. Our meta-analysis demonstrated that GLP-1RA had a superior antiobesity effect than placebo/Met in overweight/obese patients without diabetes in terms of body weight, BMI, and WC, especially for semaglutide, which had more obvious antiobesity effect and lower GI adverse events than liraglutide and exenatide.

Development and Evaluation of a Machine Learning Prediction Model for Small-for-Gestational-Age Births in Women Exposed to Radiation before Pregnancy.

Exposure to radiation has been associated with increased risk of delivering small-for-gestational-age (SGA) newborns. There are no tools to predict SGA newborns in pregnant women exposed to radiation before pregnancy. Here, we aimed to develop an array of machine learning (ML) models to predict SGA newborns in women exposed to radiation before pregnancy. Patients' data was obtained from the National Free Preconception Health Examination Project from 2010 to 2012. The data were randomly divided into a training dataset (n = 364) and a testing dataset (n = 91). Eight various ML models were compared for solving the binary classification of SGA prediction, followed by a post hoc explainability based on the SHAP model to identify and interpret the most important features that contribute to the prediction outcome. A total of 455 newborns were included, with the occurrence of 60 SGA births (13.2%). Overall, the model obtained by extreme gradient boosting (XGBoost) achieved the highest area under the receiver-operating-characteristic curve (AUC) in the testing set (0.844, 95% confidence interval (CI): 0.713-0.974). All models showed satisfied AUCs, except for the logistic regression model (AUC: 0.561, 95% CI: 0.355-0.768). After feature selection by recursive feature elimination (RFE), 15 features were included in the final prediction model using the XGBoost algorithm, with an AUC of 0.821 (95% CI: 0.650-0.993). ML algorithms can generate robust models to predict SGA newborns in pregnant women exposed to radiation before pregnancy, which may thus be used as a prediction tool for SGA newborns in high-risk pregnant women.