Development and validation of a multimodal deep learning framework for vascular cognitive impairment diagnosis.

Cerebrovascular disease (CVD) is the second leading cause of dementia worldwide. The accurate detection of vascular cognitive impairment (VCI) in CVD patients remains an unresolved challenge. We collected the clinical non-imaging data and neuroimaging data from 307 subjects with CVD. Using these data, we developed a multimodal deep learning framework that combined the vision transformer and extreme gradient boosting algorithms. The final hybrid model within the framework included only two neuroimaging features and six clinical features, demonstrating robust performance across both internal and external datasets. Furthermore, the diagnostic performance of our model on a specific dataset was demonstrated to be comparable to that of expert clinicians. Notably, our model can identify the brain regions and clinical features that significantly contribute to the VCI diagnosis, thereby enhancing transparency and interpretability. We developed an accurate and explainable clinical decision support tool to identify the presence of VCI in patients with CVD.

CT-based radiomic consensus clustering association with tumor biological behavior in clinical stage IA adenocarcinoma: a retrospective study.

Background: Research has demonstrated that radiomics models are capable of forecasting the characteristics of lung cancer. Nevertheless, due to radiomics' poor interpretability, its applicability in clinical settings remains restricted. This investigation sought to verify the correlation between radiomics features (RFs) and the biological behavior of clinical stage IA adenocarcinomas. Methods: A retrospective analysis was conducted on patients diagnosed with clinical stage IA lung adenocarcinoma who underwent resection between May 2005 and December 2018. Detailed radiomics examination of the primary tumor was carried out utilizing preoperative computed tomography (CT) images. Subsequently, patients were grouped based on their RFs using consensus clustering, enabling comparison of tumor biological characteristics among the clusters. Survival disparities among the clusters were evaluated through Kaplan-Meier and Cox analyses. Results: A consensus cluster analysis was performed on 669 patients [median age, 58 years; interquartile range (IQR), 50-64 years, 257 males, 412 females], and three distinct clusters were identified. Cluster 2 was associated with radiological solid adenocarcinoma [119 of 324 (36.7%), P<0.001], larger tumors with median tumor size of 2.1 cm with IQR of 1.7 to 2.5 cm (P<0.001), central tumor [91 of 324 (28.1%), P=0.002], pleural invasion [87 of 324 (26.9%), P<0.001], occult lymph node metastasis (ONM) [106 of 324 (32.7%), P<0.001], and a higher frequency of metastasis or recurrence [62 of 324 (19.1%), P<0.001]. The frequency of histological grade 3 was the highest in Cluster 3 [8 of 34 (23.5%), P<0.001]. Cluster 1 was associated with pure ground glass nodules (pGGNs) [184 of 310 (59.4%), P<0.001], smaller tumors with median tumor size of 1.1 cm with IQR of 0.8 to 1.4 cm (P<0.001), no pleural invasion [276 of 310 (89.0%), P<0.001], histological grade 1 [114 of 248 (46.0%), P<0.001], ONM negative [292 of 310 (94.2%), P<0.001], and a lower rate of metastasis or recurrence [298 of 310 (96.1%), P<0.001]. Conclusions: Differences in tumor biological behavior were detected among consensus clusters based on the RFs of clinical stage IA adenocarcinoma.

Serum tumor markers: potential indicators for occult lymph node metastasis in clinical T1 - 2N0M0 small cell lung cancer patients.

In their letter-to-the-editor entitled "Letter to the Editor: Incidence rate of occult lymph node metastasis in clinical T1 - 2N0M0 small cell lung cancer patients and radiomic prediction based on contrast-enhanced CT imaging: a multicenter study", Prof. Chen et al. provided insightful comments and suggestions on our original study. We appreciate the authors' feedback and have conducted a preliminary exploration of the predictive value of serum tumor markers (TMs) for occult lymph node metastasis (OLM) in clinical T1 - 2N0M0 (cT1 - 2N0M0) small cell lung cancer (SCLC) patients. The results indicate that neuron-specific enolase (NSE), carbohydrate antigen 125 (CA125), and squamous cell carcinoma antigen (SCC) have potential predictive value for detecting OLM in cT1 - 2N0M0 SCLC patients. Additionally, further exploration and confirmation through prospective, large-scale studies with robust external validation are needed.

Incidence rate of occult lymph node metastasis in clinical T1-2N0M0 small cell lung cancer patients and radiomic prediction based on contrast-enhanced CT imaging: a multicenter study : Original research.

BACKGROUND: This study aimed to explore the incidence of occult lymph node metastasis (OLM) in clinical T1 - 2N0M0 (cT1 - 2N0M0) small cell lung cancer (SCLC) patients and develop machine learning prediction models using preoperative intratumoral and peritumoral contrast-enhanced CT-based radiomic data. METHODS: By conducting a retrospective analysis involving 242 eligible patients from 4 centeres, we determined the incidence of OLM in cT1 - 2N0M0 SCLC patients. For each lesion, two ROIs were defined using the gross tumour volume (GTV) and peritumoral volume 15 mm around the tumour (PTV). By extracting a comprehensive set of 1595 enhanced CT-based radiomic features individually from the GTV and PTV, five models were constucted and we rigorously evaluated the model performance using various metrics, including the area under the curve (AUC), accuracy, sensitivity, specificity, calibration curve, and decision curve analysis (DCA). For enhanced clinical applicability, we formulated a nomogram that integrates clinical parameters and the rad_score (GTV and PTV). RESULTS: The initial investigation revealed a 33.9% OLM positivity rate in cT1 - 2N0M0 SCLC patients. Our combined model, which incorporates three radiomic features from the GTV and PTV, along with two clinical parameters (smoking status and shape), exhibited robust predictive capabilities. With a peak AUC value of 0.772 in the external validation cohort, the model outperformed the alternative models. The nomogram significantly enhanced diagnostic precision for radiologists and added substantial value to the clinical decision-making process for cT1 - 2N0M0 SCLC patients. CONCLUSIONS: The incidence of OLM in SCLC patients surpassed that in non-small cell lung cancer patients. The combined model demonstrated a notable generalization effect, effectively distinguishing between positive and negative OLMs in a noninvasive manner, thereby guiding individualized clinical decisions for patients with cT1 - 2N0M0 SCLC.

Low-intensity pulsed ultrasound reduces alveolar bone resorption during orthodontic treatment via Lamin A/C-Yes-associated protein axis in stem cells.

BACKGROUND: The bone remodeling during orthodontic treatment for malocclusion often requires a long duration of around two to three years, which also may lead to some complications such as alveolar bone resorption or tooth root resorption. Low-intensity pulsed ultrasound (LIPUS), a noninvasive physical therapy, has been shown to promote bone fracture healing. It is also reported that LIPUS could reduce the duration of orthodontic treatment; however, how LIPUS regulates the bone metabolism during the orthodontic treatment process is still unclear. AIM: To investigate the effects of LIPUS on bone remodeling in an orthodontic tooth movement (OTM) model and explore the underlying mechanisms. METHODS: A rat model of OTM was established, and alveolar bone remodeling and tooth movement rate were evaluated via micro-computed tomography and staining of tissue sections. In vitro, human bone marrow mesenchymal stem cells (hBMSCs) were isolated to detect their osteogenic differentiation potential under compression and LIPUS stimulation by quantitative reverse transcription-polymerase chain reaction, Western blot, alkaline phosphatase (ALP) staining, and Alizarin red staining. The expression of Yes-associated protein (YAP1), the actin cytoskeleton, and the Lamin A/C nucleoskeleton were detected with or without YAP1 small interfering RNA (siRNA) application via immunofluorescence. RESULTS: The force treatment inhibited the osteogenic differentiation potential of hBMSCs; moreover, the expression of osteogenesis markers, such as type 1 collagen (COL1), runt-related transcription factor 2, ALP, and osteocalcin (OCN), decreased. LIPUS could rescue the osteogenic differentiation of hBMSCs with increased expression of osteogenic marker inhibited by force. Mechanically, the expression of LaminA/C, F-actin, and YAP1 was downregulated after force treatment, which could be rescued by LIPUS. Moreover, the osteogenic differentiation of hBMSCs increased by LIPUS could be attenuated by YAP siRNA treatment. Consistently, LIPUS increased alveolar bone density and decreased vertical bone absorption in vivo. The decreased expression of COL1, OCN, and YAP1 on the compression side of the alveolar bone was partially rescued by LIPUS. CONCLUSION: LIPUS can accelerate tooth movement and reduce alveolar bone resorption by modulating the cytoskeleton-Lamin A/C-YAP axis, which may be a promising strategy to reduce the orthodontic treatment process.

A comparison of machine learning methods for radiomics modeling in prediction of occult lymph node metastasis in clinical stage IA lung adenocarcinoma patients.

Background: Accurate prediction of occult lymph node metastasis (ONM) is an important basis for determining whether lymph node (LN) dissection is necessary in clinical stage IA lung adenocarcinoma patients. The aim of this study is to determine the best machine learning algorithm for radiomics modeling and to compare the performances of the radiomics model, the clinical-radilogical model and the combined model incorporate both radiomics features and clinical-radilogical features in preoperatively predicting ONM in clinical stage IA lung adenocarcinoma patients. Methods: Patients with clinical stage IA lung adenocarcinoma undergoing curative surgery from one institution were retrospectively recruited and assigned to training and test cohorts. Radiomics features were extracted from the preoperative computed tomography (CT) images of the primary tumor. Seven machine learning algorithms were used to construct radiomics models, and the model with the best performance, evaluated using the area under the curve (AUC), was selected. Univariate and multivariate logistic regression analyses were performed on the clinical-radiological features to identify statistically significant features and to develop a clinical model. The optimal radiomics and clinical models were integrated to build a combined model, and its predictive performance was assessed using receiver operating characteristic curves, Brier score, and decision curve analysis (DCA). Results: This study included 258 patients who underwent resection (training cohort, n=182; test cohort, n=76). Six radiomics features were identified. Among the seven machine learning algorithms, extreme gradient boosting (XGB) demonstrated the highest performance for radiomics modeling, with an AUC of 0.917. The combined model improved the AUC to 0.933 and achieved a Brier score of 0.092. DCA revealed that the combined model had optimal clinical efficacy. Conclusions: The superior performance of the combined model, based on XGB algorithm in predicting ONM in patients with clinical stage IA lung adenocarcinoma, might aid surgeons in deciding whether to conduct mediastinal LN dissection and contribute to improve patients' prognosis.

Dual-energy CT-based radiomics in predicting EGFR mutation status non-invasively in lung adenocarcinoma.

Objectives: Patients with epidermal growth factor receptor (EGFR) mutations in lung adenocarcinoma (LUAD) can benefit from individualized targeted therapy. This study aims to develop, compare, analyse prediction models based on dual-energy spectral computed tomography (DESCT) and CT-based radiomic features to non-invasively predict EGFR mutation status in LUAD. Materials and methods: Patients with LUAD (n = 175), including 111 patients with and 64 patients without EGFR mutations, were enrolled in the current study. All patients were randomly divided into a training dataset (122 cases) and validation dataset (53 cases) at a ratio of 7:3. After extracting CT-based radiomic, DESCT and clinical features, we built seven prediction models and a nomogram of the best prediction. Receiver operating characteristic (ROC) curves and the mean area under the curve (AUC) values were used for comparisons among the models to obtain the best prediction model for predicting EGFR mutations. Results: The best distinguishing ability is the combined model incorporating radiomic, DESCT and clinical features for predicting the EGFR mutation status with an AUC of 0.86 (95 % CI: 0.79-0.92) in the training group and an AUC value of 0.83 (95 % CI: 0.73, 0.96) in the validation group. Conclusions: Our study provides a predictive nomogram non-invasively with a combination of CT-based radiomic, DESCT and clinical features, which can provide image-based biological information for targeted therapy of LUAD with EGFR mutations.

Response of ocean acidification to atmospheric carbon dioxide removal.

Artificial CO2 removal from the atmosphere (also referred to as negative CO2 emissions) has been proposed as a potential means to counteract anthropogenic climate change. Here we use an Earth system model to examine the response of ocean acidification to idealized atmospheric CO2 removal scenarios. In our simulations, atmospheric CO2 is assumed to increase at a rate of 1% per year to four times its pre-industrial value and then decreases to the pre-industrial level at a rate of 0.5%, 1%, 2% per year, respectively. Our results show that the annual mean state of surface ocean carbonate chemistry fields including hydrogen ion concentration ([H+]), pH and aragonite saturation state respond quickly to removal of atmospheric CO2. However, the change of seasonal cycle in carbonate chemistry lags behind the decline in atmospheric CO2. When CO2 returns to the pre-industrial level, over some parts of the ocean, relative to the pre-industrial state, the seasonal amplitude of carbonate chemistry fields is substantially larger. Simulation results also show that changes in deep ocean carbonate chemistry substantially lag behind atmospheric CO2 change. When CO2 returns to its pre-industrial value, the whole-ocean acidity measured by [H+] is 15%-18% larger than the pre-industrial level, depending on the rate of CO2 decrease. Our study demonstrates that even if atmospheric CO2 can be lowered in the future as a result of net negative CO2 emissions, the recovery of some aspects of ocean acidification would take decades to centuries, which would have important implications for the resilience of marine ecosystems.

Slim the face or not: 3D change of facial soft and hard tissues after third molars extraction: a pilot study.

BACKGROUND: Whether slim the face or not after removed third molars is the concern of some orthodontic treatment candidates. The aim of this article is to explore the volume changes of facial soft and hard tissues after third molars extraction, as well as develop a reproducible clinical protocol to precisely assess facial soft tissue volume change. METHODS: A non-randomized, non-blind, self-controlled pilot study was conducted. 24 adults aged 18-30 had ipsilateral third molars extracted. The body weight change was controlled within 2 kg. Structured light scans were taken under a standardized procedure pre-extraction (T0), three (T1), and six (T2) months post-extraction; CBCTs were taken at T0 and T2. The projection method was proposed to measure the soft tissue volume (STV) and the soft tissue volume change (STVC) by the Geomagic software. The hard tissue volume change (HTVC) was measured in the Dragonfly software. RESULTS: The final sample size is 23, including 5 males (age 26.6 ± 2.5 years) and 18 females (age 27.3 ± 2.5 years). The HTVC was - 2.33 ± 0.46ml on the extraction side. On the extraction side, the STV decreased by 1.396 (95% CI: 0.323-2.470) ml (P < 0.05) at T1, and increased by 1.753 (95% CI: -0.01-3.507) ml (P = 0.05) at T2. T2 and T0 had no difference (P > 0.05). The inter and intra-raters ICC of the projection method was 0.959 and 0.974. There was no correlation between the STVC and HTVC (P > 0.05). CONCLUSIONS: After ipsilateral wisdom teeth extraction, the volume of hard tissue on the extraction side reduces, and the volume of facial soft tissue does not change evidently. However, further research with large sample size is still needed. The STV measurement has excellent repeatability. It can be extended to other interested areas, including forehead, nose, paranasal, upper lip, lower lip and chin, which is meaningful in the field of orthodontics and orthopedics. TRIAL REGISTRATION: ChiCTR, ChiCTR1800018305 (11/09/2018), http://www.chictr.org.cn/showproj.aspx?proj=28868 .

Surgical treatment of liver inflammatory pseudotumor-like follicular dendritic cell sarcoma: A case report.

BACKGROUND: Inflammatory pseudotumor-like follicular dendritic cell sarcoma (IPT-like FDCS) is rare with a low malignant potential. Hepatic IPT-like FDCS has similar clinical features to hepatocellular carcinoma (HCC), making it extremely difficult to distinguish between them in clinical practice. We describe the case of a young female patient diagnosed with HCC before surgery, which was pathologically diagnosed as IPT-like FDCS after the left half of the liver was resected. During 6 mo of follow-up, the patient recovered well with no signs of recurrence or metastasis. CASE SUMMARY: A 23-year-old female patient with a 2-year history of hepatitis B presented to the Affiliated Hospital of Guizhou Medical University. She was asymptomatic at presentation, and the findings from routine laboratory examinations were normal except for slightly elevated alpha-fetoprotein levels. However, ultrasonography revealed a 3-cm diameter mass in the left hepatic lobe, and abdominal contrast-enhanced computed tomography revealed that the tumor had asymmetrical enhancement during the arterial phase, which declined during the portal venous phase, and had a pseudo-capsule appearance. Based on the findings from clinical assessments and imaging, the patient was diagnosed with HCC, for which she was hospitalized and had undergone laparoscopic left hepatectomy. However, the tumor specimens submitted for pathological analyses revealed IPT-like FDCS. After surgical removal of the tumor, the patient recovered. In addition, the patient continued to recover well during 6 mo of follow-up. CONCLUSION: Hepatic IPT-like FDCS is difficult to distinguish from HCC. Hepatectomy may provide beneficial outcomes in non-metastatic hepatic IPT-like FDCS.

The Value of Deep Learning Image Reconstruction in Improving the Quality of Low-Dose Chest CT Images.

This study aimed to evaluate the value of the deep learning image reconstruction (DLIR) algorithm (GE Healthcare's TrueFidelity™) in improving the image quality of low-dose computed tomography (LDCT) of the chest. First, we retrospectively extracted raw data of chest LDCT from 50 patients and reconstructed them by using model-based adaptive statistical iterative reconstruction-Veo at 50% (ASIR-V 50%) and DLIR at medium and high strengths (DLIR-M and DLIR-H). Three sets of images were obtained. Next, two radiographers measured the mean CT value/image signal and standard deviation (SD) in Hounsfield units at the region of interest (ROI) and calculated the signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR). Two radiologists subjectively evaluated the image quality using a 5-point Likert scale. The differences between the groups of data were analyzed through a repeated measures ANOVA or the Friedman test. Last, our result show that the three reconstructions did not differ significantly in signal (p > 0.05) but had significant differences in noise, SNR, and CNR (p < 0.001). The subjective scores significantly differed among the three reconstruction modalities in soft tissue (p < 0.001) but not in lung tissue (p > 0.05). DLIR-H had the best noise reduction ability and improved SNR and CNR without distorting the image texture, followed by DLIR-M and ASIR-V 50%. In summary, DLIR can provide a higher image quality at the same dose, enhancing the physicians' diagnostic confidence and improving the diagnostic efficacy of LDCT for lung cancer screening.

Stem Cells From Human Exfoliated Deciduous Teeth Alleviate Liver Cirrhosis via Inhibition of Gasdermin D-Executed Hepatocyte Pyroptosis.

Liver cirrhosis represents a type of end-stage liver disease with few effective therapies, which was characterized by damaged functional liver tissue due to long-term inflammation. Gasdermin D (GSDMD)-executed programmed necrosis is reported to be involved in inflammation. However, the role of GSDMD in liver cirrhosis remains unclear. In this study, we used a CCl4-induced cirrhosis model and found stem cells from human exfoliated deciduous teeth (SHED) infusion showed profound therapeutic effects for liver cirrhosis. Mechanistically, NLRP3 inflammasome-activated GSDMD and its pyroptosis were upregulated in liver cirrhosis, while SHED infusion could suppress the expression of GSDMD and Caspase-1, resulting in reduced hepatocyte pyroptosis and inflammatory cytokine IL-1ß release. Consistently, SHED could inhibit the elevated expression of NLRP3, GSDMD and Caspase-1 induced by CCl4 treatment in vitro co-culture system, which was mediated by decreasing reactive oxygen species (ROS) generation. Moreover, the pyroptosis inhibitor disulfiram showed similar therapeutic effects for liver cirrhosis as SHED. In conclusion, SHED alleviates CCl4-induced liver cirrhosis via inhibition of hepatocytes pyroptosis. Our findings could provide a potential treatment strategy and novel target for liver cirrhosis.

Morphologic reproducibility in 6 regions of the 3-dimensional facial models acquired by a standardized procedure: An in vivo study.

INTRODUCTION: A standardized procedure was proposed to control involuntary motion and other factors during the capture of structural light scanning that could influence the morphology of 3-dimensional facial models; interoperator reproducibility was evaluated. METHODS: Twenty subjects volunteered for facial scanning. Three researchers scanned each volunteer 3 times on the same day using the FaceScan structural light scanning system (Isravision, Darmstadt, Germany) and after the proposed procedure. Captures were done at 5-minute intervals. The 3 facial scans acquired by the same researcher were compared by reverse engineering software (Geomagic; 3D Systems, Rock Hill, SC). Six facial regions, including forehead, nose, paranasal, upper lip, lower lip and chin, and cheek, were divided. With the first scan as a reference, the other 2 scans were registered, and surface-to-surface distance maps were acquired to calculate the mean, standard deviation, and root mean squares (RMS) between 2 surfaces. The reproducibility between 3 researchers was then evaluated by a 1-way analysis of variance. RESULTS: The mean of 6 facial regions was close to 0. The RMS of lip regions were largest (0.48-0.53 mm), the forehead was smallest (0.21 mm), and the others ranged 0.37 mm to 0.42 mm. The standard deviation was slightly smaller than RMS and had the same trend of change. There was no significant difference in RMS among the 3 researchers (P >0.05). CONCLUSIONS: With the constraint of the standardized procedure, the morphologic reproducibility of facial models in 6 regions was satisfying.

Clinical and imaging features of desmoid tumors of the extremities.

BACKGROUND: Desmoid fibroma is a rare soft tissue tumor originating from the aponeurosis, fascia, and muscle, and it is also known as aponeurotic fibroma, invasive fibroma, or ligamentous fibroma. AIM: To investigate the clinical and imaging features of desmoid tumors of the extremities. METHODS: Thirteen patients with desmoid fibroma of the extremities admitted to our hospital from October 2016 to March 2021 were included. All patients underwent computed tomography (CT), magnetic resonance imaging (MRI), and pathological examination of the lesion. Data on the diameter and distribution of the lesion, the relationship between the lesion morphology and surrounding structures, MRI and CT findings, and pathological features were statistically analyzed. RESULTS: The lesion diameter ranged from 1.7 to 8.9 cm, with an average of 5.35 ± 2.39 cm. All lesions were located in the deep muscular space, with the left and right forearm each accounting for 23.08% of cases. Among the 13 patients with desmoid fibroma of the extremities, the lesions were "patchy" in 1 case, irregular in 10, and quasi-round in 2. The boundary between the lesion and surrounding soft tissue was blurred in 10 cases, and the focus infiltrated along the tissue space and invaded the adjacent structures. Furthermore, the edge of the lesion showed "beard-like" infiltration in 2 cases; bone resorption and damage were found in 8, and bending of the bone was present in 2; the boundary of the focus was clear in 1. According to the MRI examination, the lesions were larger than 5 cm (61.54%), round or fusiform in shape (84.62%), had an unclear boundary (76.92%), showed uniform signal (69.23%), inhomogeneous enhancement (84.62%), and "root" or "claw" infiltration (69.23%). Neurovascular tract invasion was present in 30.77% of cases. CT examination showed that the desmoid tumors had slightly a lower density (69.23%), higher enhancement (61.54%), and unclear boundary (84.62%); a CT value < 50 Hu was present in 53.85% of lesions, and the enhancement was uneven in 53.85% of cases. Microscopically, fibroblasts and myofibroblasts were arranged in strands and bundles, without obvious atypia but with occasional karyotyping; cells were surrounded by collagen tissue. There were disparities in the proportion of collagen tissue in different regions, with abundant collagen tissue and few tumor cells in some areas, similar to the structure of aponeuroses or ligaments, and tumor cells invading the surrounding tissues. CONCLUSION: Desmoid tumors of the extremities have certain imaging features on CT and MRI. The two imaging techniques can be combined to improve the diagnostic accuracy, achieve a comprehensive diagnosis of the disease in the clinical practice, and reduce the risk of missed diagnosis or misdiagnosis. In addition, their use can ensure timely diagnosis and treatment.

Multi-Dimensional Feature Fusion Network for No-Reference Quality Assessment of In-the-Wild Videos.

Over the past few decades, video quality assessment (VQA) has become a valuable research field. The perception of in-the-wild video quality without reference is mainly challenged by hybrid distortions with dynamic variations and the movement of the content. In order to address this barrier, we propose a no-reference video quality assessment (NR-VQA) method that adds the enhanced awareness of dynamic information to the perception of static objects. Specifically, we use convolutional networks with different dimensions to extract low-level static-dynamic fusion features for video clips and subsequently implement alignment, followed by a temporal memory module consisting of recurrent neural networks branches and fully connected (FC) branches to construct feature associations in a time series. Meanwhile, in order to simulate human visual habits, we built a parametric adaptive network structure to obtain the final score. We further validated the proposed method on four datasets (CVD2014, KoNViD-1k, LIVE-Qualcomm, and LIVE-VQC) to test the generalization ability. Extensive experiments have demonstrated that the proposed method not only outperforms other NR-VQA methods in terms of overall performance of mixed datasets but also achieves competitive performance in individual datasets compared to the existing state-of-the-art methods.

Periodontal Effect of Periodontally Accelerated Osteogenic Orthodontics in Skeletal Angle Class III: A Nonrandomized, Controlled Trial.

The objective of this study was to evaluate the effect of periodontally accelerated osteogenic orthodontics (PAOO) on gingivae and alveolar bone by analysis of clinical and cone beam computed tomography (CBCT) parameters in the treatment of 20 skeletal Class III patients. The patients included in this study were divided into test and control groups. Periodontal parameters such as probing depth (PD), gingival recession (GR), keratinized gingival width, and alveolar bone thickness of CBCT scans were measured and recorded preoperation (T0) and at 6 months postoperative (T1). The difference in PD from T0 to T1 between the two groups was not statistically significant (0.01 ± 0.46 mm vs 0.22 ± 0.65 mm, respectively; P > .05). No significant difference in GR was observed from T0 to T1 between the two groups (0.03 ± 0.26 mm vs -0.03 ± 0.27 mm, respectively; P > .05). Alveolar bone thickness (4 mm apical to the cementoenamel junction [CEJ]) change from T0 to T1 was -0.31 ± 0.35 mm for the control group and 0.06 ± 0.69 mm for the test group (P < .05). Meanwhile, alveolar bone thickness (6 mm apical to CEJ) changes from T0 to T1 were -0.38 ± 0.54 mm and 0.10 ± 0.80 mm for the control and test groups, respectively (P < .05). It was determined that PAOO in the treatment of skeletal Class III patients is effective and safe to periodontium on the basis of clinical and CBCT parameters.

Comparative transcriptomic analysis of vascular endothelial cells after hypoxia/re-oxygenation induction based on microarray technology.

OBJECTIVE: To provide comprehensive data to understand mechanisms of vascular endothelial cell (VEC) response to hypoxia/re-oxygenation. METHODS: Human umbilical vein endothelial cells (HUVECs) were employed to construct hypoxia/re-oxygenation-induced VEC transcriptome profiling. Cells incubated under 5% O2, 5% CO2, and 90% N2 for 3 h followed by 95% air and 5% CO2 for 1 h were used in the hypoxia/re-oxygenation group. Those incubated only under 95% air and 5% CO2 were used in the normoxia control group. RESULTS: By using a well-established microarray chip consisting of 58 339 probes, the study identified 372 differentially expressed genes. While part of the genes are known to be VEC hypoxia/re-oxygenation-related, serving as a good control, a large number of genes related to VEC hypoxia/re-oxygenation were identified for the first time. Through bioinformatic analysis of these genes, we identified that multiple pathways were involved in the reaction. Subsequently, we applied real-time polymerase chain reaction (PCR) and western blot techniques to validate the microarray data. It was found that the expression of apoptosis-related proteins, like pleckstrin homology-like domain family A member 1 (PHLDA1), was also consistently up-regulated in the hypoxia/re-oxygenation group. STRING analysis found that significantly differentially expressed genes SLC38A3, SLC5A5, Lnc-SLC36A4-1, and Lnc-PLEKHJ1-1 may have physical or/and functional protein-protein interactions with PHLDA1. CONCLUSIONS: The data from this study have built a foundation to develop many hypotheses to further explore the hypoxia/re-oxygenation mechanisms, an area with great clinical significance for multiple diseases.

Effects of Hypertonic Saline and Hydroxyethyl Starch on Myeloid-Derived Suppressor Cells in Hemorrhagic Shock Mice under Secondary Bacterial Attack.

OBJECTIVES: The primary target is to reveal whether the resuscitation with hypertonic saline (HTS) or hydroxyethyl starch (HES) would have different effects on the myeloid-derived suppressor cell (MDSC) count and monocytic MDSC (M-MDSC)/granulocytic/neutrophilic MDSC (G-MDSC) rate in the peripheral blood, spleen, and bone marrow nucleated cells (BMNC) in a controlled hemorrhagic shock mouse model under secondary Escherichia coli bacterial infection attack, comparing to resuscitation with normal saline (NS) in 72 hours. METHOD: After hemorrhagic shock with bacteremia, which is induced by Escherichia coli bacterial infection attack, comparing to resuscitation with normal saline (NS) in 72 hours. Method. After hemorrhagic shock with bacteremia, which is induced by Escherichia coli 35218 injection, the mice were distributed into control, NS, HTS, and HES groups. The peripheral blood nucleated cells (PBNC), spleen single-cell suspension, and bone marrow nucleated cells were collected. The flow cytometry was used to detect the MDSC, M-MDSC, and G-MDSC. RESULT: In PBNC, after resuscitation with NS, the MDSC was continuously higher, while the rate of M-MDSC/G-MDSC were continuously lower (P < 0.05). In HTS, the MDSC varied, higher at 24 and 72 hours (P < 0.05). In HTS, the MDSC varied, higher at 24 and 72 hours (P < 0.05). In HTS, the MDSC varied, higher at 24 and 72 hours (P < 0.05). In HTS, the MDSC varied, higher at 24 and 72 hours (P < 0.05). In HTS, the MDSC varied, higher at 24 and 72 hours (P < 0.05), the M-MDSC/G-MDSC were continuously lower (P < 0.05). In the spleen, resuscitation with HTS, the M-MDSC/G-MDSC were continuously lower (P < 0.05). In BMNC, after resuscitation with HES, the M-MDSC/G-MDSC were lower at 24 and 72 hours (P < 0.05). CONCLUSION: In mouse hemorrhagic shock model with bacterial infection, the resuscitation with NS, HTS, or HES induced difference changes in MDSC and M-MDSC/G-MDSC, which were time-dependent and organ-specific. Resuscitation with crystalloid, like NS or HTS, showed longer effects on the MDSC and M-MDSC/G-MDSC in peripheral blood; while HTS has a longer effect on M-MDSC/G-MDSC in the spleen, HES has a stronger impact on the differentiation regulation of MDSC to G-MDSC in the bone marrow.

Chronic spinal cord injury impairs primary CD8 T cell antiviral immunity but does not affect generation or function of memory CD8 T cells.

Antiviral immunity is severely compromised following trauma to the central nervous system. In mice with chronic spinal cord injury (SCI), primary infection with influenza virus leads to high mortality rates due to impaired expansion of virus-specific CD8 T cells. One strategy to increase resistance to viral infections is to generate memory immune cells that protect from recurrent infections. However, it is unknown if chronic SCI also impairs secondary immune responses to influenza challenge as it does primary responses. Here, we used a mouse model of chronic SCI and a clinically relevant influenza A infection to investigate CD8 T cell response. As shown previously, chronic SCI mice had impaired primary antiviral responses with high mortality rates and decreased expansion of virus-specific CD8 T cells following intranasal infection. To investigate CD8 T cell memory, we used two strains of influenza A virus [PR8(H1N1) and X31(H3N2)] that share internal proteins but differ in surface antigens. Chronic SCI mice immunized with live X31 were able to generate memory CD8 T cells that secreted IFNγ upon stimulation with viral peptides ex vivo, which was comparable to immunized uninjured mice. Importantly, immunization prior to challenge with a lethal dose of PR8 resulted in no mortality and significant CD8 T cell recall responses in both uninjured and chronic SCI mice. In addition, memory CD8 T cells generated before SCI remained functional up to 8 weeks after injury. These pre-existing memory CD8 T cells provided full protection from lethal PR8 challenge given at the chronic timepoint following injury. Overall, this study shows that memory CD8 T cells generated either before or after chronic SCI still remain functional. These results highlight the need for proper immunization of SCI patients and show the potential of memory T cells to confer protection against not only influenza, but other viral infections as well.

Morphological analysis of the alveolar bone of the anterior teeth in severe high-angle skeletal Class II and Class III malocclusions assessed with cone-beam computed tomography.

OBJECTIVE: This Cross-sectional study used cone-beam computed tomography (CBCT) to evaluate the difference in the alveolar bone of the anterior teeth between high-angle adults with severe skeletal Class II malocclusions and Class III malocclusions. MATERIALS AND METHODS: The CBCT archives from 62 high-angle adults were selected from patients of the Stomatology Hospital of Peking University between October 2017 to January 2018. The 62 high-angle adult subjects were divided into the following 2 groups based on their sagittal jaw relationships: severe skeletal Class II and severe skeletal Class III. Vertical bone level (VBL), alveolar bone area (ABA), and thickness of alveolar bone were measured at 2 mm, 4 mm, and 6 mm below and above to the cemento-enamel junction (CEJ) level, as well as at the apical level. Then, independent samples t-test were conducted for statistical comparisons. RESULTS: In the maxillary incisors, the labial VBL was smaller in the patients in skeletal Class III group than those in skeletal Class II group (P<0.05). On the labial side, the ABA was significantly thinner in patients in skeletal Class II group than those in skeletal Class III group, especially in terms of the maxillary central incisors' ABA at 4 mm and 6 mm above the CEJ level (P<0.05), in terms of apical ABA and total ABA of the maxillary lateral incisors (P<0.05). The alveolar bone thickness around maxillary lateral incisors was significantly thinner in patients of skeletal Class II than that of patients of skeletal Class III, especially regarding the apical level on the labial side (P<0.05). The ABA of the mandibular alveolar bone in the area of the lower anterior teeth was significantly thinner in patients in skeletal Class III group than those in skeletal Class II group, especially in terms of apical ABA, total ABA on the labial and lingual sides, and ABA at 6 mm below the CEJ level on the lingual side (P<0.05). In the mandibular lateral incisors, the alveolar bone thickness was significantly thinner in patients in skeletal Class III group than it was in patients in skeletal Class II group, especially regarding the apical level on the lingual side (P<0.05). CONCLUSIONS: The ABA and the alveolar bone thickness of the mandibular anterior teeth were significantly thinner in the severe high-angle group of skeletal Class III adult patients than in the sample of severe high-angle skeletal Class II adult cases. Our study firstly revealed that the roots of the maxillary central and lateral incisors were placed more labially in the subjects of severe high-angle skeletal Class II than in those of severe high-angle skeletal Class III, especially in the lateral incisors.