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Matching the maxillomandibular basal bone width is essential to the stability of orthodontic treatment. We aimed to determine the relationship between basal bone width mismatching and the vertical and sagittal skeletal pattern in patients with skeletal Class III malocclusion through shape analysis and structural equation modeling (SEM).Cone-beam computed tomography images were collected from 45 men and 51 women. Width mismatching of the basal bone was determined using generalized Procrustes analysis. Twenty-two parameters from the synthesized cephalogram were measured, followed by factor analysis and SEM.Mismatch occurred at the second molar (men, -4.29 ± 4.32 mm; women, -5.55 ± 4.43 mm) and retromolar regions (men, -8.49 ± 5.11 mm; women: -8.93 ± 5.25 mm). The sum of angles had the largest loading for vertical-1 (extracted from 18 vertical cephalometric measurements) (men, 0.9477; women, 0.9489), followed by MP-SN angle (0.9408) in men and N-Me/S-Go (0.9342) in women. Wits appraisal and anteroposterior dysplasia indicator were largest for Sagittal-1. SEM showed a positive effect of male vertical-1 and 2 on width difference in the retromolar region (P 0.001; B 0). Female vertical-1 had a significant positive effect on DW7 (P 0.001; B = 5.535) and DWR (P = 0.016; B = 3.427) as vertical-2. Sagittal-1 showed a negative correlation with DW7 in both genders (P 0.05; B 0) and with DWR in men.Basal bone width mismatching occurred at the second molar and retromolar regions, especially in low-angle and patients with severe skeletal Class III malocclusion.

Neuroblastoma (NB), which is the most common pediatric extracranial solid tumor, varies widely in its clinical presentation and outcome. NB has a unique ability to spontaneously differentiate and regress, suggesting a potential direction for therapeutic intervention. However, the underlying mechanisms of regression remain largely unknown, and more reliable prognostic biomarkers are needed for predicting trajectories for NB. We performed scRNA-seq analysis on 17 NB clinical samples and three peritumoral adrenal tissues. Primary NB displayed varied cell constitution, even among tumors of the same pathological subtype. Copy number variation patterns suggested that neuroendocrine cells represent the malignant cell type. Based on the differential expression of sets of related marker genes, a subgroup of neuroendocrine cells was identified and projected to differentiate into a subcluster of benign fibroblasts with highly expressed

Placenta accreta spectrum disorder (PASD) is a life-threatening obstetric complication. China still lacks high-quality data on the epidemiology of PASD. We intend to examine the major risk factors for PASD, explore the association of PASD with severe adverse perinatal outcomes and describe the geographical variations in China.We used data from the China Labor and Delivery Survey, which included a total of 75,132 births from 96 hospitals in 24 provinces in China in 2015 and 2016. Each participating hospital randomly selected 6-10 weeks within a 12-month period. In the selected weeks, all births with gestational age ≥24 weeks or birth weight ≥500 g were included. We analyzed the demographic characteristics and prevalence of PASD in pregnant women. Multivariable logistic regression was used to examine the association of previous caesarean section (CS) and repeated surgical abortion with PASD. We explored the association of PASD with severe adverse perinatal outcomes, which indicated by Weighted Adverse Outcome Score (WAOS) ≥ 20. Multivariable logistic regression was used to examine the association of PASD with WAOS. We also calculated and compared the prevalence of PASD in different regions of China.The weighted prevalence of PASD was 2.20% (95% CI 0.76 to 4.95) in our population，and there was a substantial difference in the prevalence of PASD by geographic regions in China. Two or more previous CS (adjusted OR 2.34, 95%CI 1.41 to 3.88) and repeated surgical abortion (twice: 2.16, 1.20 to 3.92; 3 times: 4.31, 1.70 to 10.96; ≥4 times: 4.76, 3.12 to 7.26) were significant risk factors for PASD. PASD (adjusted OR 3.77, 95% CI 2.80 to 5.06) was a significant risk factor for severe adverse perinatal outcomes indicated by WAOS score.The prevalence of PASD in China appeared higher than that in other countries, and varied substantially by geographic regions. Two or more previous CS and repeated surgical abortion were major risk factors for PASD. Pregnant women with PASD had more severe adverse pregnancy outcomes. Reducing primary cesarean section and repeated surgical abortion are the key to decreasing PASD.

Background The mitochondrial tRNA translation optimization 1 (MTO1) gene, which is closely related to defective mitochondrial oxidative phosphorylation, is an evolutionarily conserved protein expressed in high energy-demanding tissues and is associated with complex oxidative phosphorylation deficiency type 10 (COXPD10) in humans. Related cases and studies are still scarce and have not been reported in the Chinese region. Materials and methods Detailed clinical assessment was applied to the patient. Based on next-generation sequencing technology, we performed whole-exome sequencing of the patient and the parents. Sanger sequencing was used for validation. Bioinformatics software and protein simulations were used to predict the pathogenicity of the variants. Results The patient was diagnosed with a possible association with mitochondrial disease according to the clinical manifestations and physical examination. A novel frameshift mutation c.344delA (p. Asn115Thrfs*11) and a novel point mutation c.1055C > T (p. Thr352Met) in the MTO1 gene were identified. They were found to cause abnormal changes in amino acids and the protein by biochemical tools, indicating it may be pathogenic. Conclusion We present two novel and possibly pathogenic variants in the MTO1 gene in a Chinese Han family.

Caspases are often considered the final checkpoint for a pathogen to save its replicative niche from collapsing after cell death signaling has been initiated in response to infection. Two recent works (Li et al., 2021; Peng et al., 2022) found that pathogens inhibit host cell death by inactivating multiple caspases with a novel posttranslational modification.

It well known that vehicle detection is an important component of the field of object detection. However, the environment of vehicle detection is particularly sophisticated in practical processes. It is comparatively difficult to detect vehicles of various scales in traffic scene images, because the vehicles partially obscured by green belts, roadblocks or other vehicles, as well as influence of some low illumination weather. In this paper, we present a model based on Faster R–CNN with NAS optimization and feature enrichment to realize the effective detection of multi-scale vehicle targets in traffic scenes. First, we proposed a Retinex-based image adaptive correction algorithm (RIAC) to enhance the traffic images in the dataset to reduce the influence of shadow and illumination, and improve the image quality. Second, in order to improve the feature expression of the backbone network, we conducted Neural Architecture Search (NAS) on the backbone network used for feature extraction of Faster R–CNN to generate the optimal cross-layer connection to extract multi-layer features more effectively. Third, we used the object Feature Enrichment that combines the multi-layer feature information and the context information of the last layer after cross-layer connection to enrich the information of vehicle targets, and improve the robustness of the model for challenging targets such as small scale and severe occlusion. In the implementation of the model, K-means clustering algorithm was used to select the suitable anchor size for our dataset to improve the convergence speed of the model. Our model has been trained and tested on the UN-DETRAC dataset, and the obtained results indicate that our method has art-of-state detection performance.

GC-MS platform has been proved to be an important analytical technique for plasma metabolomics, but lack of efficient sample preparation strategies prior to sample injection has limited its wide application. In the present work, twenty two extraction protocols including protein precipitation (PPT), liquid-liquid extraction (LLE), solid-phase extraction (SPE) and ultrafiltration were simultaneously evaluated using non-spiked and metabolite standards spiked human plasma. Sample-to-extraction solvent ratio and metabolites derivatization conditions were also investigated and optimised. The results demonstrated that stepwise LLE protocol (MeOH–H2O/CHCl3/CHCl3–MeOH) was the most efficient extraction strategy for the combination of untargeted and targeted metabolomics. Sample-to-extraction solvent ratio of 1:3 (v:v) was found to perform better than higher solvent ratios. Also, the maximum derivatization performance was obtained when using 30 μL N-methyl-N-tri-methylsilyltrifluoroacetamide (MSTFA) and 1% trimethyl-chlorosilane (TMCS) incubated at 60 °C for 120 min. In the end, the optimised sample preparation method was applied successfully to plasma untargeted metabolomics of rheumatoid arthritis (RA) and four metabolites (gamma-butyrolactone, MG (0:0/18:0/0:0), tocopherol and oxalic acid) were found to be potential biomarkers for the diagnosis of RA.

Background: Systemic lupus erythematosus (SLE) is chronic autoimmune disease with multiple organ damage and is associated with poor prognosis and high mortality. Identification of universal biomarkers to predict SLE activity is challenging due to the heterogeneity of the disease. This study aimed to identify the indicators that are sensitive and specific to predict activity of SLE. Methods: We retrospectively analyzed 108 patients with SLE. Patients were categorized into SLE with activity and without activity groups on the basis of SLE disease activity index. We analyzed the potential of routine and novel indicators in predicting the SLE activity using receiver operating characteristic curves and multivariate logistic regression. The Spearman method was used to understand the correlation between albumin to fibrinogen ratio (AFR), prognostic nutritional index (PNI), AFR+PNI model and disease activity.Results: SLE with activity group had elevatory C3, ESR, CRP, D-dimer, fibrinogen, CRP to albumin ratio, positive rate of anti-dsDNA and ANUA, lower TBIL, TP, albumin, albumin/globulin, creatinine, HDL-C, hemoglobin, hematocrit, lymphocyte count, AFR, PNI. A further established model based on combination of AFR and PNI (AFR-PNI model) showed prominent value in distinguishing SLE with activity patients from SLE without activity patients. In addition, the sensitivity and specificity of AFR-PNI model +anti-dsDNA combination model were superior to AFR-PNI model. AFR and PNI were risk factors for SLE activity. Moreocer, AFR, PNI and AFR+PNI model correlated with disease activity. Furthermore, AFR, PNI, and AFR-PNI model were associated with fever, pleurisy, pericarditis, renal involvement. Conclusion: These findings suggest that predictive model based on combination of AFR and PNI may be useful markers to identify active SLE in clinical practice.

For the first time, a convenient, online couplable, sensitive and environmentally friendly sample pretreatment method, namely, magnetism-reinforced in-tube solid phase microextraction (MR/IT-SPME) was proposed to effectively enrich heavy metal ions (HMIs). Monolithic capillary microextraction column embedded modified Fe3O4 magnetic nanoparticles (MCEN) was conveniently synthesized and employed as the microextraction column of MR/IT-SPME. Subsequently, the MCEN was put into a magnetic coil which was utilized to exert variable magnetic field during extraction procedure. Three HMIs, including Cu(II), Co(II) and Hg(II), were selected as studied ions and reacted with chelating agent sodium diethyldithiocarbamatetrihydrate to form metallic coordination compounds. The complexes were infused to the MCEN to perform the MR/IT-SPME extraction and then online determined by high-performance liquid chromatography equipped with diode array detection (HPLC-DAD). A series of key parameters affecting the extraction performance were investigated in detail. Results revealed that the exertion of magnetic field in adsorption and desorption steps favored the adsorption and release of the coordination compounds, with the extraction efficiencies enhanced from 47-65% to 67-89%. Finally, the developed online MR/IT-SPME-HPLC-DAD approach was successfully applied to determine studied HMIs in environmental water and seafood samples. The confirmatory experiments further evidenced the reliability and feasibility of the introduced approach for the analysis of trace HMIs in complex samples.

ARID1A, a key subunit of the SWI/SNF chromatin remodeling complex, exhibits recurrent mutations in various types of human cancers, including liver cancer. However, the function of ARID1A in the pathogenesis of liver cancer remains controversial. Here, we demonstrate that Arid1a knockout may result in states of different cell differentiation, as indicated by single-cell RNA sequencing (scRNA-seq) analysis. Bulk RNA-seq also revealed that Arid1a deficiency upregulated these genes related to cell stemness and differentiation, but downregulated genes related to the hepatic functions. Furthermore, we confirmed that deficiency of Arid1a increased the expression of hepatic stem/progenitor cell markers, such as Cd133 and Epcam, and enhanced the self-renewal ability of cells. Mechanistic studies revealed that Arid1a loss remodeled the chromatin accessibility of some genes related to liver functions. Thus, Arid1a deficiency might contribute to cancer development by increasing the number of stem/progenitor-like cells through dysregulating the expression of these genes related to cell stemness, differentiation and liver functions.