Predictive nomogram of ultrasound indicators for the termination outcome of caesarean scar pregnancy.

To develop and validate a nomogram for predicting the risk of adverse events (intraoperative massive haemorrhage or retained products of conception) associated with the termination of Caesarean scar pregnancy (CSP). Data were retrospectively collected from patients diagnosed with CSP who underwent Dilation and Curettage (D&C) at two hospitals. This data was divided into internal and external cohorts for analysis.

Nurse-Authored Patents and Their Influencing Factors Analysis Among Oncology Nurses Based on the Structural Equation Model.

Aims: This study analysed the status of nurse-authored patents and their influencing factors. In particular, this study examined the effects of nurses' innovative behaviour and creative self-efficacy on nurse-authored patent output via structural equation modelling (SEM).

Design: A descriptive cross-sectional study.

Different impacts of adipose tissue dynamics on prognosis in patients with resectable locally advanced rectal cancer treated with and without neoadjuvant treatment.

Background: Body composition is recognized to be associated with clinical outcomes in patients with locally advanced rectal cancer (LARC). This study aimed to determine the prognostic role of regional adipose tissue distribution in patients with resectable LARC treated with or without neoadjuvant chemoradiotherapy (nCRT).

Methods: This retrospective study included 281 consecutive patients who underwent radical surgery for LARC with or without preoperative nCRT between 2013 and 2019.

Radiogenomic analysis based on lipid metabolism-related subset for non-invasive prediction for prognosis of renal clear cell carcinoma.

Purpose: Multiple lipid metabolism pathways alterations are associated with clear cell renal cell carcinoma (ccRCC) development and aggressiveness. In this study, we aim to develop a novel radiogenomics signature based on lipid metabolism-related genes (LMRGs) that may accurately predict ccRCC patients' survival.

Materials And Methods: First, 327 ccRCC were used to screen survival-related LMRGs and construct a gene signature based on The Cancer Genome Atlas (TCGA) database.

A fault diagnosis method for wireless sensor network nodes based on a belief rule base with adaptive attribute weights.

Due to the harsh operating environment and ultralong operating hours of wireless sensor networks (WSNs), node failures are inevitable. Ensuring the reliability of the data collected by the WSN necessitates the utmost importance of diagnosing faults in nodes within the WSN. Typically, the initial step in the fault diagnosis of WSN nodes involves extracting numerical features from neighboring nodes.

CT enterography-based radiomics combined with body composition to predict infliximab treatment failure in Crohn's disease.

Purpose: Accurately predicting the treatment response in patients with Crohn's disease (CD) receiving infliximab therapy is crucial for clinical decision-making. We aimed to construct a prediction model incorporating radiomics and body composition features derived from computed tomography (CT) enterography for identifying individuals at high risk for infliximab treatment failure.

Methods: This retrospective study included 137 patients with CD between 2015 and 2021, who were divided into a training cohort and a validation cohort with a ratio of 7:3.

Establishment and application of the BRP prognosis model for idiopathic pulmonary fibrosis.

Background: Idiopathic pulmonary fibrosis (IPF) is the most common idiopathic interstitial lung disease. Clinical models to accurately evaluate the prognosis of IPF are currently lacking. This study aimed to construct an easy-to-use and robust prediction model for transplant-free survival (TFS) of IPF based on clinical and radiological information.

Development and validation of MRI-based scoring models for predicting placental invasiveness in high-risk women for placenta accreta spectrum.

Objectives: To develop and validate MRI-based scoring models for predicting placenta accreta spectrum (PAS) invasiveness.

Materials And Methods: This retrospective study comprised a derivation cohort and a validation cohort. The derivation cohort came from a systematic review of published studies evaluating the diagnostic performance of MRI signs for PAS and/or placenta percreta in high-risk women.

Wireless Electrical Signals Induce Functional Neuronal Differentiation of BMSCs on 3D Graphene Framework Driven by Magnetic Field.

Bone marrow mesenchymal stem cells (BMSCs) are suggested as candidates for neurodegeneration therapy by autologous stem cells to overcome the lack of neural stem cells in adults. However, the differentiation of BMSCs into functional neurons is a major challenge for neurotherapy. Herein, a methodology has been proposed to induce functional neuronal differentiation of BMSCs on a conductive three-dimensional graphene framework (GFs) combined with a rotating magnetic field.

High-power, sub-100-fs, 1600-1700-nm all-fiber laser for deep multiphoton microscopy.

The 1600-1700-nm ultrafast fiber lasers attract great interests in the deep multiphoton microscopy, due to the reduced levels of the tissue scattering and absorption. Here, we report on the 86.7-MHz, 717-mW, 91.

Trimanganese Tetroxide Nanozyme protects Cartilage against Degeneration by Reducing Oxidative Stress in Osteoarthritis.

Osteoarthritis, a chronic degenerative cartilage disease, is the leading cause of movement disorders among humans. Although the specific pathogenesis and associated mechanisms remain unclear, oxidative stress-induced metabolic imbalance in chondrocytes plays a crucial role in the occurrence and development of osteoarthritis. In this study, a trimanganese tetroxide (Mn O ) nanozyme with superoxide dismutase (SOD)-like and catalase (CAT)-like activities is designed to reduce oxidative stress-induced damage and its therapeutic effect is investigated.

SS-TBN: A Semi-Supervised Tri-Branch Network for COVID-19 Screening and Lesion Segmentation.

Insufficient annotated data and minor lung lesions pose big challenges for computed tomography (CT)-aided automatic COVID-19 diagnosis at an early outbreak stage. To address this issue, we propose a Semi-Supervised Tri-Branch Network (SS-TBN). First, we develop a joint TBN model for dual-task application scenarios of image segmentation and classification such as CT-based COVID-19 diagnosis, in which pixel-level lesion segmentation and slice-level infection classification branches are simultaneously trained via lesion attention, and individual-level diagnosis branch aggregates slice-level outputs for COVID-19 screening.

Eclampsia with hypothyroidism complicated with posterior reversible encephalopathy syndrome-a case report.

Background: Posterior reversible encephalopathy syndrome (PRES) is a rare neurological disorder with complex physiopathological mechanisms that have not been fully understood. Early identification is of great prognostic significance, of which the symptoms and radiological abnormalities can be completely reversed. If the diagnosis and treatment are delayed, ischemia and massive infarction may be developed in some patients.

A fully automatic target detection and quantification strategy based on object detection convolutional neural network YOLOv3 for one-step X-ray image grading.

Methods for automatic image analysis are demanded for dealing with the explosively increased imaging data in clinics. Osteoarthritis (OA) is a typical disease diagnosed based on X-ray imaging. Herein, we propose a novel modeling strategy based on YOLO version 3 (YOLOv3) for automatic simultaneous localization of knee joints and quantification of radiographic knee OA.

CT Radiomics to Predict Macrotrabecular-Massive Subtype and Immune Status in Hepatocellular Carcinoma.

Background Macrotrabecular-massive (MTM) subtype of hepatocellular carcinoma (HCC) is an aggressive variant associated with angiogenesis and immunosuppressive tumor microenvironment, which is expected to be noninvasively identified using radiomics approaches. Purpose To construct a CT radiomics model to predict the MTM subtype and to investigate the underlying immune infiltration patterns. Materials and Methods This study included five retrospective data sets and one prospective data set from three academic medical centers between January 2015 and December 2021.

A New Topology-Switching Strategy for Fault Diagnosis of Multi-Agent Systems Based on Belief Rule Base.

Effective fault-diagnosis strategies have been the focus of research on multi-agent systems (MASs). In this paper, the belief rule base (BRB)-based distributed fault-diagnosis problem for MASs is investigated, and a topology-switching strategy is developed to increase the reliability of fault-diagnosis model. Firstly, a BRB-based distributed fault-diagnosis model is constructed for the MAS with multiple faults, then expert knowledge is used to judge whether the agent is faulty.

Treatment-related adverse events of PD-1/PD-L1 inhibitors combined with CTLA-4 inhibitors in clinical trials: a meta-analysis.

Aim: PD-1/PD-L1 inhibitors in combination with CTLA-4 inhibitors are being tested in a number of ongoing clinical trials. As a result, it is critical to fully comprehend the toxicity characteristics of adverse events in combination therapy. This study aims to extensively compare the incidences and ORs of treatment-related adverse events between two combination strategies.

Influence of different region of interest sizes on CT-based radiomics model for microvascular invasion prediction in hepatocellular carcinoma.

Objectives: Microvascular invasion (MVI) is an important predictor of postoperative recurrence or poor outcomes of hepatocellular carcinoma (HCC). Radiomics is able to predict MVI in HCC preoperatively. This study aims to investigate the influence of different region of interest (ROI) sizes on CT-based radiomics model for MVI prediction in HCC.

Overlapping syndrome of recurrent anti-N-methyl-D-aspartate receptor encephalitis and anti-myelin oligodendrocyte glycoprotein demyelinating diseases: A case report.

Background: Anti-N-methyl-D-aspartate receptor encephalitis (NMDARe) is capable of presenting a relapsing course and coexisting with myelin oligodendrocyte glycoprotein antibody disease, whereas it has been relatively rare. We describe a man with no history of tumor who successively developed anti-NMDARe and anti-myelin oligodendrocyte glycoprotein antibody disease.

Case Summary: A 29-year-old man was initially admitted with headache, fever, intermittent abnormal behavior, decreased intelligence, limb twitching and loss of consciousness on July 16, 2018.

Stem Cell Membrane-Encapsulated Zeolitic Imidazolate Framework-8: A Targeted Nano-Platform for Osteogenic Differentiation.

Mesenchymal stem cells (MSCs) have been recognized as one of the most promising pharmaceutical multipotent cells, and a key step for their wide application is to safely and efficiently regulate their activities. Various methods have been proposed to regulate the directional differentiation of MSCs during tissue regeneration, such as nanoparticles and metal ions. Herein, nanoscale zeolitic imidazolate framework-8 (ZIF-8), a Zn-based metal-organic framework, is modified to direct MSCs toward an osteoblast lineage.

Assessment of Solid Pulmonary Nodules or Masses Using Zero Echo Time MR Lung Imaging: A Prospective Head-to-Head Comparison With CT.

Objective: The aim of this study is to determine the potential of zero echo time (ZTE) MR lung imaging in the assessment of solid pulmonary nodules or masses and diagnostic consistency to CT in terms of morphologic characterization.

Methods: Our Institutional Review Board approved this prospective study. Seventy-one patients with solid pulmonary nodules or masses larger than 1 cm in diameter confirmed by chest CT were enrolled and underwent further lung ZTE-MRI scans within 7 days.

Biomimetic Metal-Organic Frameworks as Targeted Vehicles to Enhance Osteogenesis.

Although engineered nanoparticles loaded with specific growth factors are used to regulate differentiation of stem cells, the low loading efficiency and biocompatibility are still great challenges in tissue repair. A nature-inspired biomimetic delivery system with targeted functions is attractive for enhancing cell activity and controlling cell fate. Herein, a stem cell membrane (SCM)-wrapped dexamethasone (DEX)-loaded zeolitic imidazolate framework-8 (ZIF-8) is constructed, which integrates the synthetic nanomaterials with native plasma membrane, to achieve efficient DEX delivery and DEX-mediated bone repair.

Stemness Maintenance and Massproduction of Neural Stem Cells on Poly L-Lactic Acid Nanofibrous Membrane Based on Piezoelectriceffect.

Neural stem cells (NSCs) therapy is promising for treating neurodegenerative disorders and neural injuries. However, the limited in vitro expansion, spontaneous differentiation, and decrease in stemness obstruct the acquisition of high quantities of NSCs, restricting the clinical application of cell-based therapies and tissue engineering. This article reports a facile method of promoting NSCs expansion and maintaining stemness using wireless electrical stimulation triggered by piezoelectric nanomaterials.

Endowing Polyetheretherketone Implants with Osseointegration Properties: In Situ Construction of Patterned Nanorod Arrays.

Polyetheretherketone (PEEK) is widely used in orthopedic and craniomaxillofacial surgeries as it exhibits excellent biocompatibility, mechanical property, and chemical stability. However, its clinical application is limited by the biological inertness of PEEK. Numerous efforts have been made to improve the bioactivity of this polymer over the years.