Case report: Primary myelofibrosis presenting with portal hypertension mimicking cirrhosis.

Primary myelofibrosis (PMF) is an infrequent etiology of noncirrhotic portal hypertension (PH). In clinical settings, non-cirrhotic PH is often misdiagnosed as cirrhotic PH. This case report details a patient who exhibited recurrent esophageal variceal hemorrhage and was initially misdiagnosed with cirrhosis. Initially poised for liver transplantation, the patient's liver biopsy revealed no significant cirrhosis but showed signs of extramedullary hematopoiesis (EMH). Following the accurate diagnosis of PMF, the patient underwent standard treatment, leading to an absence of recurrent gastrointestinal hemorrhage due to esophageal varices for nearly three years.

Exploring Research on the Construction and Application of Knowledge Graphs for Aircraft Fault Diagnosis.

Fault diagnosis is crucial for repairing aircraft and ensuring their proper functioning. However, with the higher complexity of aircraft, some traditional diagnosis methods that rely on experience are becoming less effective. Therefore, this paper explores the construction and application of an aircraft fault knowledge graph to improve the efficiency of fault diagnosis for maintenance engineers. Firstly, this paper analyzes the knowledge elements required for aircraft fault diagnosis, and defines a schema layer of a fault knowledge graph. Secondly, with deep learning as the main method and heuristic rules as the auxiliary method, fault knowledge is extracted from structured and unstructured fault data, and a fault knowledge graph for a certain type of craft is constructed. Finally, a fault question-answering system based on a fault knowledge graph was developed, which can accurately answer questions from maintenance engineers. The practical implementation of our proposed methodology highlights how knowledge graphs provide an effective means of managing aircraft fault knowledge, ultimately assisting engineers in identifying fault roots accurately and quickly.

Swimming start model and determination of the optimal breakout position.

While many parameters contribute to swimming start performance, a few have been proven to affect the overall start performance more significantly than others; these include take-off velocity, flight time, entry water distance, time underwater during descent and ascent, and free-swimming velocity. This study aims to analyse the influential trajectory of these key parameters on the overall start performance, particularly focusing on determining the optimal breakout point. Ten national-level swimmers participated in this study, which combined kinematics and statistical analysis to propose a novel start model that can be used to explore the influential trajectory of key parameters on the overall start performance and assess the effect of some training factors for performance improvement. Further, this study investigated the optimal breakout position via a mathematical model. This is the first study to provide a solution to determine this parameter. The solution is verified to be practical through trial data, and the overall start performance is improved by 0.71-3.29%, depending on the swimmer's current level. Therefore, the results can be used as a reference for swimming start training and improvement.

A Deep-Learning-Based Real-Time Detector for Grape Leaf Diseases Using Improved Convolutional Neural Networks.

Black rot, Black measles, Leaf blight and Mites of grape are four common grape leaf diseases that seriously affect grape yield. However, the existing research lacks a real-time detecting method for grape leaf diseases, which cannot guarantee the healthy growth of grape plants. In this article, a real-time detector for grape leaf diseases based on improved deep convolutional neural networks is proposed. This article first expands the grape leaf disease images through digital image processing technology, constructing the grape leaf disease dataset (GLDD). Based on GLDD and the Faster R-CNN detection algorithm, a deep-learning-based Faster DR-IACNN model with higher feature extraction capability is presented for detecting grape leaf diseases by introducing the Inception-v1 module, Inception-ResNet-v2 module and SE-blocks. The experimental results show that the detection model Faster DR-IACNN achieves a precision of 81.1% mAP on GLDD, and the detection speed reaches 15.01 FPS. This research indicates that the real-time detector Faster DR-IACNN based on deep learning provides a feasible solution for the diagnosis of grape leaf diseases and provides guidance for the detection of other plant diseases.

Analysis of risk factors for multiple primary oral squamous cell carcinoma: a cohort study.

OBJECTIVE: Chewing betel quid (CBQ) is popular in Southeast Asia, resulting in a high incidence of oral squamous cell carcinoma (OSCC). The incidence of multiple primary oral cancer (MPOC) has gradually increased and has become one of the main causes of OSCC treatment failure. However, it is unclear whether the high incidence of MPOC is also correlated with the habit of CBQ. MATERIALS AND METHODS: In this retrospective study, 915 OSCC patients were enrolled. MPOC incidence and characteristics were analyzed. CBQ and other risk factors for MPOC were investigated by chi-squared test and logistic stepwise regression analysis. RESULTS: Among 915 patients, 15 were diagnosed with synchronous MPOC. After follow-up, 60 of 915 patients developed a second or third primary lesion site and were diagnosed with metachronous MPOC. The remaining 840 patients were then diagnosed with single primary oral cancer (SPOC). The cumulative incidence of MPOC in all OSCC patients was 8.2%. CBQ and the related oral submucous fibrosis (OSF) were found to be independent risk factors of MPOC (P < 0.001). Both MPOC and SPOC patients with a CBQ habit were much younger than those who did not have a CBQ habit (P < 0.001). The buccal mucosa was the most common primary occurrence site (35.9%) in MPOC cases, and almost all MPOC patients with buccal cancer had previously suffered from OSF (88.9%). CONCLUSION: CBQ and CBQ-related OSF, for the first time, are identified as the independent risk factors of MPOC. Prevention and treatment of OSF as well as cessation of CBQ are expected to become new approaches to reduce the incidence of MPOC. CLINICAL RELEVANCE: More frequent physical examinations should be undertaken in OSCC patients with CBQ or CBQ-related OSF.

A distributed quantile estimation algorithm of heavy-tailed distribution with massive datasets.

Quantile estimation with big data is still a challenging problem in statistics. In this paper we introduce a distributed algorithm for estimating high quantiles of heavy-tailed distributions with massive datasets. The key idea of the algorithm is to apply the alternating direction method of multipliers in parameter estimation of the generalized pareto distribution in a distributed structure and compute high quantiles based on parameter estimation by the Peak Over Threshold method. This paper proves that the proposed algorithm converges to a stationary solution when the step size is properly chosen. The numerical study and real data analysis also shows that the algorithm is feasible and efficient for estimating high quantiles of heavy-tailed distribution with massive datasets and there is a clear-cut winner for the extreme quantiles.

Mineralocorticoid receptor antagonism limits experimental choroidal neovascularization and structural changes associated with neovascular age-related macular degeneration.

Choroidal neovascularization (CNV) is a major cause of visual impairment in patients suffering from wet age-related macular degeneration (AMD), particularly when refractory to intraocular anti-VEGF injections. Here we report that treatment with the oral mineralocorticoid receptor (MR) antagonist spironolactone reduces signs of CNV in patients refractory to anti-VEGF treatment. In animal models of wet AMD, pharmacological inhibition of the MR pathway or endothelial-specific deletion of MR inhibits CNV through VEGF-independent mechanisms, in part through upregulation of the extracellular matrix protein decorin. Intravitreal injections of spironolactone-loaded microspheres and systemic delivery lead to similar reductions in CNV. Together, our work suggests MR inhibition as a novel therapeutic option for wet AMD patients unresponsive to anti-VEGF drugs.