Triage method for endometrial biopsy in postmenopausal women: a multicenter retrospective cohort study.

OBJECTIVE: To identify the optimal triage procedure for endometrial biopsies in postmenopausal women. METHODS: The clinical information of 470 postmenopausal women with endometrial biopsy results and postmenopausal bleeding (PMB) and/or transvaginal ultrasonography (TVU) abnormalities were collected at the gynecology departments of four general hospitals from March 2021 to March 2022. In the validation cohort, 112 women with TVU abnormalities who underwent endometrial biopsy at Xiangya hospital between May 2022 and May 2023 were enrolled. The endpoint was the final diagnosis based on hysteroscopy reports and biopsy pathology results. The sensitivity, specificity, positive predictive value, and negative predictive value were compared among the three triage methods. A nomogram prediction model was developed and validated. RESULTS: Referring women with TVU abnormalities for endometrial biopsy identified 100% malignant/premalignant lesions despite low specificity (19.7%). Among women with measurable endometrial thickness (ET), we suggest that the ET cutoff value for biopsy referral should be ≥4 mm. The PMB (odds ratio [OR], 3.241; 95% confidence interval [CI], 1.073-9.789), diabetes (OR, 10.915; 95% CI, 3.389-35.156), and endometrial thickness (OR, 1.277; 95% CI, 1.156-1.409) were independent predictive factors for endometrial (pre)malignancy. A nomogram prediction model was constructed (area under curve [AUC] = 0.802, 95% CI: 0.715 to 0.889). The ideal cutoff point was 22.5, with a sensitivity of 100.0% and a specificity of 15.7%. The external validation achieved an AUC of 0.798 (95% CI, 0.685-0.911). CONCLUSIONS: It was possible to refer all postmenopausal women with TVU abnormity (ET ≥ 4 mm or other abnormal findings) for endometrial biopsy. Among women with TVU abnormalities, a nomogram was constructed, and a score greater than 22.5 suggested the need for referral for endometrial biopsy, while a score less than 22.5 suggested that regular follow-up was required, further improving the triage procedure.

Quantifying evapotranspiration fluxes on green roofs: A comparative analysis of observational methods.

Evapotranspiration (ET) is an important process in green stormwater infrastructure (GSI) aiming to reduce urban drainage, to promote cooling and/or to contribute to an urban hydrological balance restoration closer to the natural one. However, on these structures and particularly on green roofs (GR), its evaluation remains challenging and subject to discussion. Estimates of ET by water balance, energy balance, and an ET chamber were performed on five different plots of a full-scale experimental green roof in Trappes (France). Compared to both water balance (90th percentile range of daily ET values: 0.8 mm/d to 3 mm/d) and chamber methods (90th percentile range of daily ET values: 1 mm/d to 1.5 mm/d), the energy balance (90th percentile range of daily ET values is between 1.8 mm and 3.7 mm) produces higher values, 1 to 2 times higher in cumulative values during common periods. The chamber ET displays a similar trend to the energy balance on an hourly basis, and its values remain within the same range as the water balance evaluations on a daily time-step. All three assessments consistently fell below the potential ET values estimated with the Penman-Monteith formula. Critical issues in ET estimation through experimentation have arisen. Sensible heat flux (H) significantly increases ET values when using the energy balance approach compared to the other two methods. The Water Balance method is practical, but on days following rainfall events, the Chamber method may prove more reliable, albeit more time and labour-intensive. The three methods indicated that the substrate thickness was the main contributing factor to increase ET, with well-maintained herbaceous plants providing higher ET values than sedums in thick (15 cm) substrates. In addition, the substrate's nature, especially its organic content, is another factor that promotes ET in green roofs.

Big Data Analytics on Lung Cancer Diagnosis Framework With Deep Learning.

As the segment of diseased tissue in PET images is time-consuming, laborious and low accuracy, this work proposes an automated framework for PET image screening, denoising and diseased tissue segmentation. First, taking into account the characteristics of PET images, the framework uses a differential activation filter to select whole-body images containing lesion tissue. Second, a new neural network containing residual connections which has powerful generalization performance compared with normal FCN network is proposed for PET image reconstruction and denoising. Finally, in the segmentation of lesion tissues, a custom clustering algorithm based on the density is used to distinguishe the lesion tissue part from the normal tissue. Tests on real medical PET images show that the whole automated framework has good performance and time cost in PET lesion image screening, image denoising and lesion tissue segmentation compared with other algorithms. The framework shows promising scientific study and application prospects.

Circ_0000029 Interacts with the miR-576-5p/KCNA1 Axis to Hamper the Development of Pediatric Asthma in an Asthma-Like in vitro Assessment.

OBJECTIVE: Numerous circular RNAs (circRNAs) have been verified to execute crucial roles in "asthma-like" progression of the airway smooth muscle cells (ASMCs). The present study aimed to scrutinize the function and mechanism of circ_0000029 in pediatric asthma etiology in vitro. METHODS: A cell model of asthma was developed using ASMCs induced by platelet-derived growth factor BB (PDGF-BB). Western blotting and qRT-PCR were performed to determine the expression levels of circ_0000029, miR-576-5p, and KCNA1 in PDGF-BB-treated ASMCs. Dual-luciferase reporter, RNA-binding protein immunoprecipitation, and RNA pull-down experiments were conducted to validate targeting relationships. CCK-8 and Transwell assays were performed to evaluate the proliferative and migratory potential of ASMCs. The rate of apoptosis was analyzed using flow cytometry. RESULTS: Pronounced circ_0000029 and KCNA1 downregulation and high levels of miR-576-5p were observed in PDGF-BB-treated ASMCs. Circ_0000029 targets miR-576-5p to regulate KCNA1 expression. The loss of KCNA1 and upregulation of miR-576-5p dramatically impeded apoptosis but promoted ASMC migration and proliferation. Ectopic expression of circ_0000029 manifested the opposite outcome among ASMCs. Furthermore, KCNA1 deficiency and miR-576-5p upregulation counteracted the effects of circ_0000029 overexpression on ASMCs. CONCLUSIONS: Circ_0000029 represses the abnormal migration and growth of ASMCs by mediating miR-576-5p and KCNA1 expression levels. This suggests that the regulatory axis circ_0000029/miR-576-5p/KCNA1 is a potential target for pediatric asthma treatment.

Pharmacological network analysis of the functions and mechanism of kaempferol from Du Zhong in intervertebral disc degeneration (IDD).

Background: Senescence and apoptosis of the nucleus pulposus cells (NPCs) are essential components of the intervertebral disc degeneration (IDD) process. Senescence and anti-apoptosis treatments could be effective ways to delay or even stop disc degeneration. IDD has been treated with Eucommia ulmoides Oliver (Du Zhong, DZ) and its active ingredients. However, the roles and mechanisms of DZ in NPC apoptosis and senescence remain unclear. Methods: Traditional Chinese Medicine Systems Pharmacology (TCMSP) database was used to select the main active ingredients of DZ with the threshold of oral bioavailability (OB) â€‹≥ â€‹30% and drug-likeness (DL) â€‹≥ â€‹0.2. GSE34095 contained expression profile of degenerative intervertebral disc tissues and non-degenerative intervertebral disc tissues were downloaded for different expression genes analysis. The disease targets genes of IDD were retrieved from GeneCards. The online tool Metascape was used for functional enrichment annotation analysis. The specific effects of the ingredient on IL-1ß treated NPC cell proliferation, cell senescence, reactive oxygen species (ROS) accumulation and cell apoptosis were determined by CCK-8, SA-ß-gal staining, flowcytometry and western blot assays. Results: A total of 8 active compounds of DZ were found to meet the threshold of OB â€‹≥ â€‹30% and DL â€‹≥ â€‹0.2 with 4151 drug targets. After the intersection of 879 IDD disease targets obtained from GeneCards and 230 DEGs obtained from the IDD-related GSE dataset, a total of 13 hub genes overlapped. According to functional enrichment annotation analysis by Metascape, these genes showed to be dramatically enriched in AGE-RAGE signaling, proteoglycans in cancer, wound healing, transmembrane receptor protein tyrosine kinase signaling, MAPK cascades, ERK1/2 cascades, PI3K/Akt signaling pathway, skeletal system, etc. Disease association analysis by DisGeNET indicated that these genes were significantly associated with IDD, intervertebral disc disease, skeletal dysplasia, and other diseases. Active ingredients-targets-signaling pathway networks were constructed by Cytoscape, and kaempferol was identified as the hub active compound of DZ. In the IL-1ß-induced IDD in vitro model, kaempferol treatment significantly improved IL-1ß-induced NPC cell viability suppression and senescence. In addition, kaempferol treatment significantly attenuated IL-1ß-induced ROS accumulation and apoptosis. Furthermore, kaempferol treatment partially eliminated IL-1ß-induced decreases in aggrecan, collagen II, SOX9, and FN1 levels and increases in MMP3, MMP13, ADAMTS-4, and ADAMTS-5. Moreover, kaempferol treatment significantly relieved the promotive effects of IL-1ß stimulation upon p38, JNK, and ERK1/2 phosphorylation. ERK1/2 inhibitor PD0325901 further enhanced the effect of kaempferol on the inhibition of ERK1/2 phosphorylation, downregulation of MMP3 and ADAMTS-4 expression, and upregulation of aggrecan and collagen II expressions. Conclusion: Kaempferol has been regarded as the major active compound of DZ, protecting NPCs from IL-1ß-induced damages through promoting cell viability, inhibiting cell senescence and apoptosis, increasing ECM production, and decreasing ECM degradation. MAPK signaling pathway may be involved. The translational poteintial of this article: This study provides in vitro experimental data support for the pharmacological effects of kaempferol in treating IDD, and lays a solid experimental foundation for its future clinical application in IDD treatment.

FOXO3-Activated circFGFBP1 Inhibits Extracellular Matrix Degradation and Nucleus Pulposus Cell Death via miR-9-5p/BMP2 Axis in Intervertebral Disc Degeneration In Vivo and In Vitro.

(1) Background: intervertebral disc degeneration (IVDD) defined as the degenerative changes in intervertebral disc is characterized by extracellular matrix (ECM) degradation and death in nucleus pulposus (NP) cells. (2) Methods: The model of IVDD was established in male Sprague Dawley rats using a puncture of a 21-gauge needle at the endplates located in the L4/5 intervertebral disc. Primary NP cells were stimulated by 10 ng/mL IL-1ß for 24 h to mimic IVDD impairment in vitro. (3) Results: circFGFBP1 was downregulated in the IVDD samples. circFGFBP1 upregulation inhibited apoptosis and extracellular matrix (ECM) degradation and promoted proliferation in IL-1ß-stimulated NP cells. Additionally, circFGFBP1 upregulation mitigated the loss of NP tissue and the destruction of the intervertebral disc structure in vivo during IVDD. FOXO3 could bind to the circFGFBP1 promoter to enhance its expression. circFGFBP1 upregulated BMP2 expression in NP via sponging miR-9-5p. FOXO3 enhanced the protection of circFGFBP1 in IL-1ß-stimulated NP cells, whereas a miR-9-5p increase partly reversed the protection. miR-9-5p downregulation contributed to the survival of IL-1ß-stimulated NP cells, which was partially reversed by BMP2 silence. (4) Conclusions: FOXO3 could activate the transcription of circFGFBP1 via binding to its promoter, which resulted in the enhancement of BMP2 via sponging miR-9-5p and then inhibited apoptosis and ECM degradation in NP cells during IVDD.

Case report: Targeting the PD-1 receptor and genetic mutations validated in primary histiocytic sarcoma with hemophagocytic lymphohistiocytosis.

Histiocytic sarcoma (HS) is a rare hematological malignancy with limited treatment options, and it is also prone to complications such as hemophagocytic lymphohistiocytosis (HLH) in the later stages of the disease, leading to difficulties in treatment and poor prognosis. It highlights the importance of developing novel therapeutic agents. Herein, we present a case of a 45-year-old male patient who was diagnosed with PD-L1-positive HS with HLH. The patient was admitted to our hospital with recurrent high fever, multiple skin rashes with pruritus throughout the body and enlarged lymph nodes. Subsequently, pathological biopsy of the lymph nodes revealed high expression of CD163, CD68, S100, Lys and CD34 in the tumor cells and no expression of CD1a and CD207, confirming this rare clinical diagnosis. Concerning the low remission rate by conventional treatment in this disease, the patient was administered with sintilimab (an anti-programmed cell death 1 [anti-PD-1] monoclonal antibody) at 200 mg/d combined with a first-line chemotherapy regimen for one cycle. Further exploration of pathological biopsy by using next-generation gene sequencing led to the use of targeted therapy of chidamide. After one cycle of combination therapy (chidamide+sintilimab, abbreviated as CS), the patient achieved a favorable response. The patient showed remarkable improvement in the general symptoms and laboratory examination results (e.g., elevated indicators of inflammation); even the clinical benefits was not persistent, he survived one more month after his cessation of treatment by himself due to economic difficulty. Our case suggests that PD-1 inhibitor coupled with targeted therapy might constitute a potential therapeutic option for primary HS with HLH.

A Residual Fusion Network for Osteosarcoma MRI Image Segmentation in Developing Countries.

Among primary bone cancers, osteosarcoma is the most common, peaking between the ages of a child's rapid bone growth and adolescence. The diagnosis of osteosarcoma requires observing the radiological appearance of the infected bones. A common approach is MRI, but the manual diagnosis of MRI images is prone to observer bias and inaccuracy and is rather time consuming. The MRI images of osteosarcoma contain semantic messages in several different resolutions, which are often ignored by current segmentation techniques, leading to low generalizability and accuracy. In the meantime, the boundaries between osteosarcoma and bones or other tissues are sometimes too ambiguous to separate, making it a challenging job for inexperienced doctors to draw a line between them. In this paper, we propose using a multiscale residual fusion network to handle the MRI images. We placed a novel subnetwork after the encoders to exchange information between the feature maps of different resolutions, to fuse the information they contain. The outputs are then directed to both the decoders and a shape flow block, used for improving the spatial accuracy of the segmentation map. We tested over 80,000 osteosarcoma MRI images from the PET-CT center of a well-known hospital in China. Our approach can significantly improve the effectiveness of the semantic segmentation of osteosarcoma images. Our method has higher F1, DSC, and IOU compared with other models while maintaining the number of parameters and FLOPS.

A Cascaded Multi-Stage Framework for Automatic Detection and Segmentation of Pulmonary Nodules in Developing Countries.

Lung cancer has the highest mortality rate among all malignancies. Non-micro pulmonary nodules are the primary manifestation of early-stage lung cancer. If patients can be detected with nodules in the early stage and receive timely treatment, their survival rate can be improved. Due to the large number of patients and limited medical resources, doctors take a longer time to make a diagnosis, which reduces efficiency and accuracy. Besides, there are no suitable approaches for developing countries. Therefore, we propose a 2.5D-based cascaded multi-stage framework for automatic detection and segmentation (DS-CMSF) of pulmonary nodules. The first three stages of the framework are used to discover lesions, and the latter stage is used to segment them. The first locating stage introduces the classical 2D-based Yolov5 model to locate the nodules roughly on axial slices. The second aggregation stage proposes a candidate nodule selection (CNS) algorithm to locate further and reduce redundant candidate nodules. The third classification stage uses a multi-size 3D-based fusion model to accommodate nodules of varying sizes and shapes for false-positive reducing. The last segmentation stage introduces multi-scale and attention modules into 3D-based UNet autoencoder to segment the nodular regions finely. Our proposed framework achieves 95.95% sensitivity and 89.50% CPM for nodules detection on the LUNA16 dataset, and 86.75% DSC for nodules segmentation on the LIDC-IDRI dataset. Moreover, our approach also achieves the accuracy-complexity trade-off, which can effectively realize the auxiliary diagnosis of pulmonary nodules in developing countries.

DNMT1/miR-130a/ZEB1 Regulatory Pathway Affects the Inflammatory Response in Lipopolysaccharide-Induced Sepsis.

Sepsis is a global health care issue that affects millions of people. DNA methyltransferase I (DNMT1)-mediated DNA methylation is involved in a number of human diseases by affecting many types of cellular progression events. However, the role and underlying molecular mechanism of DNMT1 in development of sepsis remain largely unknown. Lipopolysaccharide (LPS) induced lung fibrosis in the sepsis mouse model, and DNMT1 was upregulated in lung tissues of a sepsis mouse model compared with lung tissues from control mice. Then, this study demonstrated that LPS induced the production of interleukin (IL)-7 and tumor necrosis factor (TNF)-α and promoted DNMT1 expression in primary type II alveolar epithelial cells (AECII cells). Knockdown of DNMT1 inhibited IL-7 and TNF-α secretion in AECII cells exposed to LPS. Further study demonstrated that DNMT1 repressed the expression of miR-130a in AECII cells with or without LPS exposure. Next, this study demonstrated that miR-130a inhibited ZEB1 expression in AECII cells exposed to LPS. Ultimately, this study revealed the role of the DNMT1/miR-130a/ZEB1 regulatory pathway in AECII cells exposed to LPS. Overall, our data revealed that LPS induced the secretion of inflammatory factors by modulating the DNMT1/miR-130a/ZEB1 regulatory pathway in AECII cells, thus providing a novel theoretical basis that might be beneficial for establishment of diagnostic and therapeutic strategies for sepsis.

Human pulmonary artery smooth muscle cell dysfunction is regulated by miR-509-5p in hypoxic environment.

Reportedly, dysfunction of human pulmonary arterial smooth muscle cells (PASMCs) is associated with the pathogenesis of pulmonary arterial hypertension (PAH). Herein, the role of miR-509-5p in hypoxia-induced PASMCs and the underlying mechanism were explored. PASMCs were cultured under both normoxia and hypoxia conditions. Quantitative real-time polymerase-chain reaction (qPCR) was employed for quantifying the expressions of miR-509-5p and DNMT1 mRNA in the serum of PAH patients and PASMCs. MiR-509-5p mimics and inhibitors were then, respectively, transfected into PAMSCs, and CCK-8 and Transwell assays were utilized to detect PASMCs' proliferation and migration. Flow cytometry was executed for evaluating PASMCs' apoptosis. Interrelation between miR-509-5p and DNMT1 was determined utilizing bioinformatics analysis and dual-luciferase reporter assay. Western blot assay was used to detect the expression of DNMT1 or SOD2. MiR-509-5p in serum samples of patients with PAH as well as hypoxia-induced PASMCs was significantly down-regulated, whereas DNMT1 was markedly up-regulated. MiR-509-5p mimics reduces the proliferation and migration of PASMCs, but promotes the apoptosis; conversely, miR-509-5p inhibitors exerted opposite effects. DNMT1 was identified as a target gene of miR-509-5p, and overexpression of DNMT1 reversed the biological functions of miR-509-5p in regulating the phenotypes of PAMSCs. MiR-509-5p up-regulated the expression of SOD2 by down-regulating DNMT1. MiR-509-5p regulates the proliferation, migration and apoptosis of PASMCs, and restoration of miR-509-5p may be a promising strategy to treat PAH.

A Staging Auxiliary Diagnosis Model for Nonsmall Cell Lung Cancer Based on the Intelligent Medical System.

At present, human health is threatened by many diseases, and lung cancer is one of the most dangerous tumors that threaten human life. In most developing countries, due to the large population and lack of medical resources, it is difficult for doctors to meet patients' needs for medical treatment only by relying on the manual diagnosis. Based on massive medical information, the intelligent decision-making system has played a great role in assisting doctors in analyzing patients' conditions, improving the accuracy of clinical diagnosis, and reducing the workload of medical staff. This article is based on the data of 8,920 nonsmall cell lung cancer patients collected by different medical systems in three hospitals in China. Based on the intelligent medical system, on the basis of the intelligent medical system, this paper constructs a nonsmall cell lung cancer staging auxiliary diagnosis model based on convolutional neural network (CNNSAD). CNNSAD converts patient medical records into word sequences, uses convolutional neural networks to extract semantic features from patient medical records, and combines dynamic sampling and transfer learning technology to construct a balanced data set. The experimental results show that the model is superior to other methods in terms of accuracy, recall, and precision. When the number of samples reaches 3000, the accuracy of the system will reach over 80%, which can effectively realize the auxiliary diagnosis of nonsmall cell lung cancer and combine dynamic sampling and migration learning techniques to train nonsmall cell lung cancer staging auxiliary diagnosis models, which can effectively achieve the auxiliary diagnosis of nonsmall cell lung cancer. The simulation results show that the model is better than the other methods in the experiment in terms of accuracy, recall, and precision.

A Multiprocessing Scheme for PET Image Pre-Screening, Noise Reduction, Segmentation and Lesion Partitioning.

OBJECTIVE: Accurate segmentation and partitioning of lesions in PET images provide computer-aided procedures and doctors with parameters for tumour diagnosis, staging and prognosis. Currently, PET segmentation and lesion partitioning are manually measured by radiologists, which is time consuming and laborious, and tedious manual procedures might lead to inaccurate measurement results. Therefore, we designed a new automatic multiprocessing scheme for PET image pre-screening, noise reduction, segmentation and lesion partitioning in this study. PET image pre-screening can reduce the time cost of noise reduction, segmentation and lesion partitioning methods, and denoising can enhance both quantitative metrics and visual quality for better segmentation accuracy. For pre-screening, we propose a new differential activation filter (DAF) to screen the lesion images from whole-body scanning. For noise reduction, neural network inverse (NN inverse) as the inverse transformation of generalized Anscombe transformation (GAT), which does not depend on the distribution of residual noise, was presented to improve the SNR of images. For segmentation and lesion partitioning, definition density peak clustering (DDPC) was proposed to realize instance segmentation of lesion and normal tissue with unsupervised images, which helped reduce the cost of density calculation and completely deleted the cluster halo. The experimental results of clinical data demonstrate that our proposed methods have good results and better performance in noise reduction, segmentation and lesion partitioning compared with state-of-the-art methods.

Auxiliary Medical Decision System for Prostate Cancer Based on Ensemble Method.

Prostate cancer (PCa) is one of the main diseases that endanger men's health worldwide. In developing countries, due to the large number of patients and the lack of medical resources, there is a big conflict between doctors and patients. To solve this problem, an auxiliary medical decision system for prostate cancer was constructed. The system used six relevant tumor markers as the input features and employed classical machine learning models (support vector machine and artificial neural network). Stacking method aimed at different ensemble models together was used for the reduction of overfitting. 1,933,535 patient information items had been collected from three first-class hospitals in the past five years to train the model. The result showed that the auxiliary medical system could make use of massive data. Its performance is continuously improved as the amount of data increases. Based on the system and collected data, statistics on the incidence of prostate cancer in the past five years were carried out. In the end, influence of diet habit and genetic inheritance for prostate cancer was analyzed. Results revealed the increasing prevalence of PCa and great negative impact caused by high-fat diet and genetic inheritance.

Kinetic magnetic resonance imaging analysis of thoracolumbar segmental mobility in patients without significant spondylosis.

To observe thoracolumbar segmental mobility using kinetic magnetic resonance imaging (kMRI) in patients with minimal thoracolumbar spondylosis and establish normal values for translational and angular segmental motion as well as the relative contribution of each segment to total thoracolumbar segmental motion in order to obtain a more complete understanding of this segmental motion in healthy and pathological conditions.Mid-sagittal images obtained by weight-bearing, multi-position kMRI in patients with symptomatic low back pain or radiculopathy were reviewed. The translational motion and angular variation of each segment from T10-L2 were calculated using MRAnalyzer Automated software. Only patients with a Pfirrmann grade of I or II, indicating minimal disc disease, for all thoracolumbar discs from T10-T11 to L1-L2 were included for further analysis.The mean translational motion measurements for each level of the lumbar spine were 1.15 mm at T10-T11, 1.20 mm at T11-T12, 1.23 mm at T12-L1, and 1.34 mm at L1-L2 (P < .05 for L1-L2 vs T10-T11). The mean angular motion measurements at each level were 3.26° at T10-T11, 3.92° at T11-T12, 4.95° at T12-L1, and 6.85° at L1-L2. The L1-L2 segment had significantly more angular motion than all other levels (P < .05). The mean percentage contribution of each level to the total angular mobility of the thoracolumbar spine was highest at L1-L2 (36.1%) and least at T10-T11 (17.1%; P < .01).Segmental motion was greatest in the proximal lumbar levels, and angular motion showed a gradually increasing trend from T10 to L2.

Hamartoma of Mature Cardiac Myocytes Mimicking Malignancy on 18F-FDG PET/CT Images.

Hamartoma of mature cardiac myocytes is an extremely rare type of benign cardiac tumor with a slow growth rate and generally occurs in adults. We report a case with hamartoma of mature cardiac myocytes of the right auricle demonstrating intense F-FDG uptake and a large amount of pericardial effusion on PET/CT mimicking malignancy in a 41-year-old man. Hamartoma of mature cardiac myocytes should be considered among the differential diagnoses when an F-FDG-avid primary focal cardiac mass is found in patients with malignant features on PET/CT imaging.

Hospital evaluation mechanism based on mobile health for IoT system in social networks.

The uneven distribution of medical resources is a serious problem in developing countries. Those seeking timely treatment have difficulty choosing the right hospital. To found sustainable development with medical system, this paper establishes a model of the hospital confidence evaluation index by combining national evaluation and a third-party evaluation. The model is applied to a social network. Users from any region can use the model through APP in IoT, a hospital analysis index query, which selects the best hospital for diagnosis and treatment. The model can locate different personnel characteristics by modifying the control variables. Establishing a medical system with big data provides good model characteristics. Effective data analysis through large data users in the sample is established to provide the most effective hospital recommendation, which is a good solution to the selectivity problem. The contributions in this works are: (1) Models of initial trust and hospital evaluations are established by combining national and third-party assessments; (2) the initial trust evaluation model is modified and optimized by establishing control variables; (3) the trust evaluation mechanism of users in social networks is obtained through big data sampling and model analysis, and the balanced distribution of the medical staff is realized.

Bone morphogenetic protein 2 alleviated intervertebral disc degeneration through mediating the degradation of ECM and apoptosis of nucleus pulposus cells via the PI3K/Akt pathway.

The present study aimed to explore the underlying mechanisms of bone morphogenetic protein 2 (BMP2) in alleviating intervertebral disc degeneration (IDD). A rat puncture IDD model was constructed, and the rats were randomly divided into six groups: Control; IDD (model); IDD+PBS [containing 1010 adeno­associated virus serotype 2 (AAV)]; and IDD + AAV2­BMP2 (106, 108 and 1010). IL­1ß was used to treat primary nucleus pulposus (NP) cells to mimic IDD in vitro. The effects of BMP2 in IDD were determined by magnetic resonance imaging (MRI), hematoxylin and eosin staining and Alcian Blue staining in vivo. The levels of collagen II, aggrecan, transcription factor SOX9 (SOX9) and matrix metalloproteinase 13 (MMP­13) were examined using western blot analysis and reverse transcription quantitative polymerase chain reaction (RT­qPCR) in NP tissues and cells. The expression of C­telopeptide of type II collagen (CTX­II) in the sera or cell supernatants was determined by ELISA. In addition, the levels of phosphorylation of phosphoinositide 3­kinase (PI3K) and protein kinase B (Akt), and the levels of apoptosis­associated proteins and apoptosis ratio of NP cells were also determined by western blot analysis and flow cytometry, respectively. LY29400, an inhibitor of PI3K, was used to additionally confirm the signal pathway mechanism of BMP2 treatment in IDD. BMP2 significantly extended the interval between discs and alleviated the fibrous ring rupture and the decrease in the levels of glycoproteins in IDD rats, as determined by MRI and histological staining. Additionally, BMP2 treatment significantly upregulated the levels of collagen II, aggrecan and SOX9, but downregulated the levels of MMP­13 and CTX­II in IDD rats and NP cells in a dose­dependent manner. Concurrently, recombinant human (rh)BMP2 pretreatment also significantly decreased the apoptosis ratio of interleukin (IL)­1ß­treated NP cells via downregulating the level of cleaved caspase­3 and upregulating the level of uncleaved poly (adenosine 5'­diphosphate­ribose) polymerase. It was demonstrated that rhBMP2 also significantly decreased the inflammatory response in NP tissues and cells, based on levels of IL­6, TNF­α and IL­10. In addition, rhBMP2 inhibited cell apoptosis via upregulating the phosphorylation levels of the PI3K/Akt signaling pathway, and LY29400 pretreatment inhibited the effects of BMP2 in IL­1ß treated NP cells. BMP2 alleviated IDD via the PI3K/Akt signaling pathway by inhibiting NP cell apoptosis and decreasing the levels of matrix proteins.

Diffuse hepatic epithelioid hemangioendothelioma with multiple splenic metastasis and delayed multifocal bone metastasis after liver transplantation on FDG PET/CT images: A case report.

RATIONALE: Malignant hepatic epithelioid hemangioendotheliom (HEH) is a rare vascular tumor of endothelial origin, with multiple metastases to the spleen. This report describes a diffuse HEH with splenic metastasis on 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography/computed tomography (PET/CT) images and delayed mutifocal bone metastasis after liver transplantation (LTx). PATIENT CONCERNS: A 30-year-old male was admitted to our hospital with a complaint of abdominal distension, fatigue, and anorexia for 2 months. DIAGNOSES: Mild to moderate FDG uptake in the whole liver, and multifocal FDG uptake in the spleen were observed on 18F-FDG PET/CT scan. Ultrasound guided liver biopsy was performed, and a diagnosis of HEH was confirmed. INTERVENTIONS: The patient underwent LTx and splenectomy. OUTCOMES: The patient developed low back pain due to unknown etiology, 3 months after surgery. A follow-up 18F-FDG PET/CT scan demonstrated multifocal bone destruction. Unfortunately, the patient died 12 months after surgery. LESSONS: It is noteworthy that despite liver transplantation for the treatment of HEH, there may be a risk of recurrence. For these patients with extrahepatic lesions, adjuvant chemotherapy may be a useful alternative treatment method for the prevention of recurrence.

Decision based on big data research for non-small cell lung cancer in medical artificial system in developing country.

Non-small cell lung cancer (NSCLC) is a high risk cancer and is usually scanned by PET-CT for testing, predicting and then give the treatment methods. However, in the actual hospital system, at least 640 images must be generated for each patient through PET-CT scanning. Especially in developing countries, a huge number of patients in NSCLC are attended by doctors. Artificial system can predict and make decision rapidly. According to explore and research artificial medical system, the selection of artificial observations also can result in low work efficiency for doctors. In this study, data information of 2,789,675 patients in three hospitals in China are collected, compiled, and used as the research basis; these data are obtained through image acquisition and diagnostic parameter machine decision-making method on the basis of the machine diagnosis and medical system design model of adjuvant therapy. By combining image and diagnostic parameters, the machine decision diagnosis auxiliary algorithm is established. Experimental result shows that the accuracy has reached 77% in NSCLC.