Analysis of therapeutic effects of congenital kyphosis in children due to anterior vertebral bone bridges.

Objective: To investigate the choice of treatment options and long-term orthopedic results of congenital kyphosis in children due to anterior vertebral bone bridges. Methods: The clinical data of children with congenital kyphosis due to anterior vertebral bridges treated at our center from May 2005 to May 2020 were retrospectively analyzed. We evaluated the clinical features of the deformity, the choice of treatment plan, the change in the Cobb angle of the kyphosis and the improvement of the sagittal trunk deviation before and after treatment and at the final follow-up visit by means of pre-treatment and post-treatment imaging, physical examination and analysis of the case data. Results: A total of 35 children were included. Clinical follow-up was conducted on a cohort of 5 children, all of whom presented with type Ⅱ congenital kyphosis caused by less than three thoracic anterior bone bridges. The study findings revealed no noteworthy advancement in segmental kyphosis, thoracic kyphosis, lumbar lordosis, and sagittal vertical axis during the final follow-up assessment (p > 0.05). In a cohort of 30 pediatric patients who underwent surgical intervention, segmental kyphosis was corrected, with a decrease from an average angle of (40.1 ± 20.5)° to (15.6 ± 9.5)°. Furthermore, significant improvements were noted in segmental kyphosis, thoracic kyphosis, lumbar lordosis, and sagittal vertical axis at the postoperative stage compared to the preoperative stage (p < 0.05). Notably, improvements in thoracic kyphosis and lumbar lordosis persisted at the final follow-up visit compared to postoperative (p < 0.05). Conclusion: Type Ⅱ congenital kyphosis in children caused by anterior bony bridges of less than three vertebrae in the thoracic segment can be followed up for a long period, and type Ⅱ/Ⅲ congenital kyphosis caused by anterior bony bridges of the vertebrae in the thoracolumbar, lumbar, and lumbosacral segments requires early surgery.

Relationships between the gut microbiome and brain functional alterations in first-episode, drug-naïve patients with major depressive disorder.

OBJECTIVE: Increasing evidence has shown that the microbiota-gut-brain axis (MGB) is involved in the mechanism of major depressive disorder (MDD). However, the relationship between the gut microbiome and brain function in MDD patients has not been determined. Here, we intend to identify specific changes in the gut microbiome and brain function in first-episode, drug-naïve MDD patients and then explore the associations between the two omics to elucidate how the MGB axis plays a role in MDD development. METHODS: We recruited 38 first-episode, drug-naïve MDD patients and 37 healthy controls (HC). The composition of the fecal microbiome and neural spontaneous activity alterations were examined using 16S rRNA gene amplicon sequencing analysis and regional homogeneity (ReHo). Spearman correlation analyses were conducted to assess the associations between the gut microbiome and brain function. RESULTS: Compared with HC, MDD patients exhibited distinct alterations in the gut microbiota and elevated ReHo in the frontal regions. In the MDD group, a positive relationship was noted between the relative abundance of Blautia and the HAMD-17 and HAMA scores, as well as between the relative abundance of Oxalobacteraceae and the HAMD-17 score. The relative abundances of Porphyromonadaceae and Parabacteroides were negatively correlated with the ReHo values of frontal regions. LIMITATIONS: Our study utilized a cross-sectional design, and the number of subjects was relatively small. CONCLUSION: We found that some specific gut microbiomes were associated with frontal function, and others were associated with clinical symptoms in MDD patients, which may support the role of the MGB axis underlying MDD.

Effects of tefluthrin and guadipyr on the midgut bacteria of adult Apis mellifera.

The objective of this study is to assess the potential impact of tefluthrin and guadipyr on the gut microbial composition and metabolism in adult Apis mellifera ligustica, thereby elucidating the underlying mechanisms of insecticide action and its practical implications for bee protection. In this investigation, A. mellifera were subjected to one of three dietary conditions: (1) control sugar water, (2) tefluthrin-infused sugar water, or (3) guadipyr-infused sugar water. After a 10-day exposure period, genomic DNA from the gut bacteria was extracted. High-throughput sequencing was employed to evaluate the potential influence of tefluthrin and guadipyr treatments on the diversity and abundance of gut bacteria. Among the A. mellifera specimens, a total of twenty species of gut bacteria were identified, spanning across five phyla, six classes, eleven orders, eleven families, and fifteen genera. The dominant phyla within the gut bacterial community were Proteobacteria and Bacteroidetes. In comparison to the control group, both the tefluthrin-treated and deltamethrin-treated groups exhibited alterations in the composition of their gut bacterial flora. At the phylum level, there was a significant decrease in the relative abundance of Cyanobacteria (P < 0.05). On the genus level, the tefluthrin group displayed a significant increase in the relative abundance of Bartonella and Serratia (P < 0.05). In the guadipyr-treated group, the relative abundance of Gilliamella and Frischella increased significantly (P < 0.05), while the relative abundance of norank_o_Chloroplast and Enterobacter decreased significantly (P < 0.05). Further analysis of cluster of orthologous genes predicted functional changes in gut microbial metabolism following tefluthrin exposure but no significant changes after guadipyr exposure. Consequently, exposure to tefluthrin and guadipyr can induce shifts in both the composition and metabolic activity of the gut bacteria in A. mellifera. Notably, the impact of tefluthrin on the gut bacteria of A. mellifera appears to be more pronounced compared to that of guadipyr.

Gender differences in plasma S100B levels of patients with major depressive disorder.

BACKGROUND: Low concentrations of S100B have neurotrophic effects and can promote nerve growth and repair, which plays an essential role in the pathophysiological and histopathological alterations of major depressive disorder (MDD) during disease development. Studies have shown that plasma S100B levels are altered in patients with MDD. In this study, we investigated whether the plasma S100B levels in MDD differ between genders. METHODS: We studied 235 healthy controls (HCs) (90 males and 145 females) and 185 MDD patients (65 males and 120 females). Plasma S100B levels were detected via multifactor assay. The Mahalanobis distance method was used to detect the outliers of plasma S100B levels in the HC and MDD groups. The Kolmogorov-Smirnov test was used to test the normality of six groups of S100B samples. The Mann-Whitney test and Scheirer-Ray-Hare test were used for the comparison of S100B between diagnoses and genders, and the presence of a relationship between plasma S100B levels and demographic details or clinical traits was assessed using Spearman correlation analysis. RESULTS: All individuals in the HC group had plasma S100B levels that were significantly greater than those in the MDD group. In the MDD group, males presented significantly higher plasma S100B levels than females. In the male group, the plasma S100B levels in the HC group were significantly higher than those in the MDD group, while in the female group, no significant difference was found between the HC and MDD groups. In the male MDD subgroup, there was a positive correlation between plasma S100B levels and years of education. In the female MDD subgroup, there were negative correlations between plasma S100B levels and age and suicidal ideation. CONCLUSIONS: In summary, plasma S100B levels vary with gender and are decreased in MDD patients, which may be related to pathological alterations in glial cells.

Effect of Process Parameters on Welding Residual Stress of 316L Stainless Steel Pipe.

316L stainless steel pipes are widely used in the storage and transportation of low-temperature media due to their excellent low-temperature mechanical properties and corrosion resistance. However, due to their low thermal conductivity and large coefficient of linear expansion, they often lead to significant welding residual tensile stress and thermal cracks in the weld seam. This also poses many challenges for their secure and reliable applications. In order to effectively control the crack defects caused by stress concentration near the heat-affected zone of the weld, this paper establishes a thermal elastoplastic three-dimensional finite element (FE) model, constructs a welding heat source, and simulates and studies the influence of process parameters on the residual stress around the pipeline circumference and axial direction in the heat-affected zone. Comparison and verification were conducted using simulation and experimental methods, respectively, proving the rationality of the finite element model establishment. The axial and circumferential residual stress distribution obtained by the simulation method did not have an average deviation of more than 30 MPa from the numerical values obtained by the experimental method. This study also considers the effects of welding energy, welding speed, and welding start position on the pipe's circumferential and axial residual stress laws. The results indicate that changes in welding energy and welding speed have almost no effect on the longitudinal residual stress but have a more significant effect on the transverse residual stress. The maximum transverse residual stress is reached at a welding energy of 1007.4~859.3 J/mm and a welding speed of 6.6 mm/s. Various interlayer arc-striking deflection angles can impact the cyclic phase angle of the transverse residual stress distribution in the seam center, but they do not alter its cyclic pattern. They do influence the amplitude and distribution of the longitudinal residual stress along the circumference. The residual stress distribution on the surface of the pipe fitting is homogenized and improved at 120°.

MicroRNA-877-5p promotes osteoblast differentiation by targeting EIF4G2 expression.

Stimulating bone formation potentially suggests therapeutics for orthopedic diseases including osteoporosis and osteoarthritis. Osteoblasts are key to bone remodeling because they act as the only bone-forming cells. miR-877-5p has a chondrocyte-improving function in osteoarthritis, but its effect on osteoblast differentiation is unknown. Here, miR-877-5p-mediated osteoblast differentiation was studied. Real-time reverse transcriptase-polymerase chain reaction was performed to measure miR-877-5p expression during the osteogenic differentiation of MC3T3-E1 cells. Osteoblast markers, including alkaline phosphatase (ALP), collagen type I a1 chain, and osteopontin, were measured and detected by alizarin red staining and ALP staining. Potential targets of miR-877-5p were predicted from three different algorithms: starBase ( http://starbase.sysu.edu.cn/ ), PITA ( http://genie.weizmann.ac.il/pubs/mir07/mir07_data.html ), and miRanda ( http://www.microrna.org/microrna/home.do ). It was further verified by dual luciferase reporter gene assay. The experimental results found that miR-877-5p was upregulated during the osteogenic differentiation of MC3T3-E1 cells. Overexpression of miR-877-5p promoted osteogenic differentiation, which was characterized by increased cell mineralization, ALP activity, and osteogenesis-related gene expression. Knockdown of miR-877-5p produced the opposite result. Dual luciferase reporter gene assay showed that miR-877-5p directly targeted eukaryotic translation initiation factor 4γ2 (EIF4G2). Overexpression of EIF4G2 inhibited osteogenic differentiation and reversed the promoting effect of overexpression of miR-135-5p on osteogenic differentiation. These results indicate that miR-877-5p might have a therapeutic application related to its promotion of bone formation through targeting EIF4G2.

Identifying misdiagnosed bipolar disorder using support vector machine: feature selection based on fMRI of follow-up confirmed affective disorders.

Nearly a quarter of bipolar disorder (BD) patients were misdiagnosed as major depressive disorder (MDD) patients, which cannot be corrected until mania/hypomania develops. It is important to recognize these obstacles so that the appropriate treatment can be initiated. Thus, we sought to distinguish patients with BD from MDD, especially to identify misdiagnosed BD before mania/hypomania, and further explore potential trait features that allow accurate differential diagnosis independent of state matters. Functional magnetic resonance imaging scans were performed at baseline on 92 MDD patients and 48 BD patients. The MDD patients were then followed up for more than two years. After follow-up, 23 patients transformed into BD (tBD), and 69 patients whose diagnoses remained unchanged were eligible for unipolar depression (UD). A support vector machine classifier was trained on the amygdala-based functional connectivity (FC) of 48 BD and 50 UD patients using a novel region-based feature selection. Then, the classifier was tested on the dataset, encompassing tBD and the remaining UD. It performed well for known BD and UD and can also distinguish tBD from UD with an accuracy of 81%, sensitivity of 82.6%, specificity of 79%, and AUC of 74.6%, respectively. Feature selection results revealed that ten regions within the cortico-limbic neural circuit contributed most to classification. Furthermore, in the FC comparisons among diseases, BD and tBD shared almost overlapped FC patterns in the cortico-limbic neural circuit, and both of them presented pronounced differences in most regions within the circuit compared with UD. The FC values of the most discriminating brain regions had no prominent correlations with the severity of depression, anxiety, and mania/hypomania (FDR correction). It suggests that BD possesses some trait features in the cortico-limbic neural circuit, rendering it dichotomized by the classifier based on known-diagnosis data.

Evaluation of physical education teaching effect using Random Forest model under artificial intelligence.

This work aims to optimize the physical education (PE) teaching effect based on deep learning (DL) to cultivate high-level college students better. Firstly, the present situation of college teachers' teaching ability is surveyed to realize the deficiencies in teaching. Secondly, an optimization algorithm is proposed to improve the node splitting mode. This algorithm can solve the problem of single and similar node splitting modes in the Random Forest (RF) algorithm. The independent node splitting method Iterative Dichotomiser 3 and Classification and Regression Tree in the algorithm are recombined, and new splitting rules are obtained through adaptive parameter selection. Finally, the scheme designed is tested. The results suggest: The results suggest: (1) During the training of the proposed algorithm, although the loss curve at 4550 and 6800 points has a small crest, the error of the network loss function shows a downward trend and tends to be flat; (2) Compared with unoptimized Genetic Algorithm (GA) and Genetic Algorithm-Back Propagation (GA-BP), the proposed algorithm shows better performance both in terms of time consumption and accuracy (time consumption is less than 5.4 ms, and accuracy is more than 95 %). In a word, using the GA-BP-RF algorithm proposed to improve the PE teaching effect is feasible. The proposed model provides ideas for applying DL technology to improve teachers' teaching abilities.

Enhancement of multilayer lithium storage in a ß12-borophene/graphene heterostructure with built-in dipoles.

The combination of borophene with a supporting metallic layer is beneficial in stabilizing its structure and promoting its application in energy storage. Here, through first-principles calculations, we screen a ß12-borophene/graphene (ß12-B/G) heterostructure with superior structural integrity, strong interlayer binding, and high thermodynamic stability among different B/G heterostructures. Besides, it is noteworthy that ß12-B/G has been recently synthesized, further opening the possibility of expanding its use in energy storage. Then the selected target is systematically investigated as an anode material for lithium-ion batteries (LIBs). Compared with each monolayer component, multiple lithium-ion adsorption is achieved in the ß12-B/G heterostructure, resulting in an ultra-high theoretical specific capacity of 2267 mA h g-1. In addition, a lower diffusion energy barrier indicates faster electron transport and lithium-ion diffusion in the ß12-B/G heterostructure. Notably, the multilayer lithium adsorption avoids the formation of dendritic deposits, as evidenced by complete ionization of the cationic layers. Moreover, the disparity in the work functions of the individual layers gives rise to a built-in dipole in ß12-B/G, further enhancing the multilayer lithium storage and ion migration. All these results suggest that the construction of borophene-based heterostructures with built-in dipoles is a feasible way to design high-performance LIB anode materials.

Identifying the source and fate of boron in geothermal water: Evidence from B/Na and B isotopes.

High level dissolved B, which poses risks to human health, has been widely observed in geothermal water. In the Guide Basin, NW China, a series of geothermal water samples along a fault show a wide range of B contents ranging from 3.14 to 8.33 mg/L, which are higher than the WHO Guideline value equaling 2.4 mg/L in drinking water. To identify the sources and fate of B, we conduct a comprehensive analysis of hydrochemistry and stable isotopes (D, 18O and 11B) of three thermal fields representing three stages of hydrogeochemical evolution (stages I, II and III). From stage I to III, there are trends of increasing mineral dissolution, which is supported by increasing mean reservoir temperature and concentrations of conservative elements (Cl, Na, K, Li and Si). Geothermal water in stage I with meteoric origin and the lowest reservoir temperature has the highest B/Na resulting from silicate dissolution and falls on the mixing line between granitoids and cold water on the plot of δ11B versus 1/B, showing the control of silicate dissolution. However, geothermal water in stage III has lower Ca, B Sr and B/Na than that in stage II. Because of the occurrence of other processes, geothermal water in stages II and III deviates from the LMWL. Compared with geothermal water in stage I, the increased Sr/Ca and decreased B/Ca show that B are removed by both coprecipitation and vapor separation. With the aid of B isotopes, we find vapor separation dominates in stage II, whereas carbonate precipitation dominates in stage III. Overall, a combined use of three isotopes (H, O and B) and three element ratios (B/Na, B/Ca and Sr/Ca) leads to a complete understanding of B cycle and hydrogeochemical evolution in hydrothermal systems.

Advances in genetic factors of adolescent idiopathic scoliosis: a bibliometric analysis.

Objective: This study offers a bibliometric analysis of the current situation, hotspots, and cutting-edge domains of genetic factors of adolescent idiopathic scoliosis (AIS). Methods: All publications related to genetic factors of AIS from January 1, 1992, to February 28, 2023, were searched from the Web of Science. CiteSpace software was employed for bibliometric analysis, collecting information about countries, institutions, authors, journals, and keywords of each article. Results: A cumulative number of 308 articles have been ascertained. Since 2006, publications relating to genetic factors of AIS have significantly increased. China leads in both productivity and influence in this area, with the Chinese Academy of Medical Sciences being the most productive institution. The most prolific scholars in this field are Y. Qiu and Z. Z. Zhu. The publications that contributed the most were from Spine and European Spine Journal. The most prominent keywords in the genetic factors of AIS were "fibrillin gene", "menarche", "calmodulin", "estrogen receptor gene", "linkage analysis", "disc degeneration", "bone mineral density", "melatonin signaling dysfunction", "collagen gene", "mesenchymal stem cell", "LBX1", "promoter polymorphism", "Bone formation", "cerebrospinal fluid flow" and "extracellular matrix". Conclusion: This analysis provides the frontiers and trends of genetic factors in AIS, including relevant research, partners, institutions and countries.