Publications by authors named "Minglei Li"

mushrooms are esteemed as a rare and highly valuable resource for both culinary and medicinal purposes. Ancient medical classics have documented their beneficial effects on conditions such as indigestion, loss of appetite, and neurological disorders. Modern phytochemical research into their secondary metabolites has led to the discovery of numerous bioactive compounds with significant biological activities.

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Purpose: To summarize our treatment experience of acute urethral trauma in pre-pubertal girls.

Methods: We retrospectively analyzed six pre-pubertal girls with acute severe urethral trauma who were admitted to our hospital from April 2003 to April 2023 and followed up.

Results: All six patients had pelvic fractures and vaginal injuries, and one had a rectal injury.

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This study presents the first comprehensive genomic analysis of , a classical folk medicine and newly identified macrofungus from the Qinling Mountains. Utilizing advanced sequencing technologies, including PacBio HiFi and Hi-C, we achieved a high-quality chromosome-level genome assembly. The genome, sized at 39.

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Bone disorders affect more than half of the adult population worldwide who may have a poor quality of life and physical independence worldwide. Multi-omic techniques are increasingly adopted and applied to determine the molecular mechanisms of bone tissue repair, providing perspective towards personalized medical intervention. Data from genomics, epigenomics, transcriptomics, proteomics, glycomics, and lipidomics were combined to elucidate dynamic processes in bone repair.

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Background: The incremental prognostic value of integrating myocardial cine radiomics into predictive models for major adverse cardiovascular events (MACE) risk in patients with ST-elevation myocardial infarction (STEMI) is unclear.

Purpose: To determine if myocardial cine radiomics can improve risk assessment for MACE when combined with clinical information and cardiac MRI parameters in STEMI patients.

Study Type: Retrospective.

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Autoimmune cerebellar ataxia (ACA) is a cerebellar syndrome induced by autoimmune reactions and its onset is induced by malignant tumors, prodromic infection, and gluten allergy. Its clinical symptoms include gait disorder, limb ataxia, dysarthria, and dysphagia. According to , the diagnosis of ACA is based on the following points: 1.

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Background: To analyze the clinical characteristics, complications and patients satisfaction of MIP hypospadias variant.

Methods: A retrospective analysis was performed for 31 patients with MIP admitted to our hospital from January 2008 to February 2023. All enrolled patients underwent telephone follow-up and a survey was conducted on the satisfaction of patients and their families.

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In cell or droplet separation, high acoustic wave energy of a surface acoustic wave (SAW) device is required to generate sufficient acoustic radiation force. In this paper, the electrode width-control floating electrode focused unidirectional interdigital transducer (EWC-FEFUDT) is proposed due to its enhanced focusing properties. The performance of the EWC-FEFUDT is investigated using the Coupling-of-Mode (COM) theory, and the COM parameter is extracted using the Finite Element Method (FEM).

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mushroom is a nutritionally rich and rare edible fungus. The traditional cultivation model, which relies on expanding the cultivation area to meet market demand, is no longer sufficient to address the rapidly growing market demand. Enhancing the yield and quality of without increasing the cultivation area is an intractable challenge in the development of the mushroom industry.

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Introduction: The Steinberg classification system is commonly used by orthopedic surgeons to stage the severity of patients with osteonecrosis of the femoral head (ONFH), and it includes mild, moderate, and severe grading of each stage based on the area of the femoral head affected. However, clinicians mostly grade approximately by visual assessment or not at all. To accurately distinguish the mild, moderate, or severe grade of early stage ONFH, we propose a convolutional neural network (CNN) based on magnetic resonance imaging (MRI) of the hip joint of patients to accurately grade and aid diagnosis of ONFH.

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Introduction: Bronchoscopy is of great significance in diagnosing and treating respiratory illness. Using deep learning, a diagnostic system for bronchoscopy images can improve the accuracy of tracheal, bronchial, and pulmonary disease diagnoses for physicians and ensure timely pathological or etiological examinations for patients. Improving the diagnostic accuracy of the algorithms remains the key to this technology.

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Motivation: Exploring the association between drugs and targets is essential for drug discovery and repurposing. Comparing with the traditional methods that regard the exploration as a binary classification task, predicting the drug-target binding affinity can provide more specific information. Many studies work based on the assumption that similar drugs may interact with the same target.

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Purpose: Parastomal hernia (PH) is a frequent complication following radical cystectomy and ileal conduit. The purpose of this study was to summarize the clinical experience and technical characteristics of laparoscopic Sugarbaker repair of PH following radical cystectomy and ileal conduit.

Methods: We retrospectively evaluated all patients who underwent laparoscopic treatment of PH following radical cystectomy and ileal conduit at Huashan Hospital, Fudan University from May 2013 to December 2022.

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Purpose: To review the safety and efficacy of Lap-re-Do technique in the treatment of large parastomal hernia.

Methods: We retrospectively analyzed the recurrence and complications of 81 patients with large parastomal hernia who underwent Lap-re-Do technique in Huashan Hospital of Fudan University from May 2010 to December 2019. And the patients should be able to complete follow-up.

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Background: Neurospecific Enolase (NSE), a multifunctional protein, is present in various tissues of the body and plays an important role in many disease processes, such as infection, inflammation, tumours, injury, and immunity. In recent years, the application of NSE in respiratory diseases has become increasingly widespread and a research hotspot.

Objective: This study aims to explore the relationship between NSE and childhood pneumonia, providing assistance for the diagnosis and assessment of pneumonia.

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Proteolysis-targeting chimera (PROTAC) has become a very important means of protein degradation and a new way of disease treatment. In particular, PROTACs constructed with ligands for E3 ligase cereblon account for more than 90 % of the PROTACs currently in clinical research. Notably, CRBN ligands themselves are a class of molecular glue compounds capable of degrading neo-substrate proteins.

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Crushing waste concrete and using it directly as RAs has the disadvantages of high porosity and high water absorption. To achieve the reuse of resources, the researchers use microbial mineralization methods to further reinforce RAs. In this paper, the effect of the microbial carbonic anhydrase mineralization method on the water absorption of RAs was investigated, and the macroscopic analysis was performed by determining the indexes of water absorption and apparent density of RAs before and after the modification, and the microscopic analysis of RAs by using the methods of SEM, XRD, DSC, and EDS as well.

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Background: Concomitant anterior urethral valves (AUVs) and posterior urethral valves (PUVs) is an extremely rare congenital urologic anomaly, which may be easily overlooked in the clinic.

Objective: This study assessed the prognosis of children with concomitant PUVs and AUVs.

Methods: The clinical data of inpatients with concomitant AUVs and PUVs in our hospital were collected from January 1983 to June 2022.

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Introduction: Mixed gonadal dysgenesis (MGD) is a rare disorder of sexual development. The management of MGD is challenging since the disease significantly impacts a patient's growth, hormone balance, and gonadal development. This article used a large population and a long follow-up period for its analysis.

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Early detection and accurate identification of thyroid nodules are the major challenges in controlling and treating thyroid cancer that can be difficult even for expert physicians. Currently, many computer-aided diagnosis (CAD) systems have been developed to assist this clinical process. However, most of these systems are unable to well capture geometrically diverse thyroid nodule representations from ultrasound images with subtle and various characteristic differences, resulting in suboptimal diagnosis and lack of clinical interpretability, which may affect their credibility in the clinic.

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Bronchoscopy plays a crucial role in diagnosing and treating lung diseases. The deep learning-based diagnostic system for bronchoscopic images can assist physicians in accurately and efficiently diagnosing lung diseases, enabling patients to undergo timely pathological examinations and receive appropriate treatment. However, the existing diagnostic methods overlook the utilization of prior knowledge of medical images, and the limited feature extraction capability hinders precise focus on lesion regions, consequently affecting the overall diagnostic effectiveness.

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Background: To develop a fully automated CNN detection system based on magnetic resonance imaging (MRI) for ACL injury, and to explore the feasibility of CNN for ACL injury detection on MRI images.

Methods: Including 313 patients aged 16 - 65 years old, the raw data are 368 pieces with injured ACL and 100 pieces with intact ACL. By adding flipping, rotation, scaling and other methods to expand the data, the final data set is 630 pieces including 355 pieces of injured ACL and 275 pieces of intact ACL.

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Many powerful computational methods based on graph neural networks (GNNs) have been proposed to predict drug-protein interactions (DPIs). It can effectively reduce laboratory workload and the cost of drug discovery and drug repurposing. However, many clinical functions of drugs and proteins are unknown due to their unobserved indications.

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Objective: The objective of this study is to develop a novel automatic convolutional neural network (CNN) that aids in the diagnosis of meniscus injury, while enabling the visualization of lesion characteristics. This will improve the accuracy and reduce diagnosis times.

Methods: We presented a cascaded-progressive convolutional neural network (C-PCNN) method for diagnosing meniscus injuries using magnetic resonance imaging (MRI).

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Knee segmentation and landmark localization from 3D MRI are two significant tasks for diagnosis and treatment of knee diseases. With the development of deep learning, Convolutional Neural Network (CNN) based methods have become the mainstream. However, the existing CNN methods are mostly single-task methods.

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