Publications by authors named "Meng Di"

This article aims to explore the clinical characteristics and corresponding nursing points of elderly patients with massive hiatal hernia. A case study of an elderly patient with massive hiatal hernia and severe cardiopulmonary disease was reviewed, along with relevant literature. Nursing points are the following: multidisciplinary team to estimate surgical risks and develop individualized pre-rehabilitation management strategies; assessment and intervention for thrombosis and bleeding risks; postoperative hemodynamic monitoring and precise fluid management; dynamic observation of inflammatory indicators and infection prevention and care; and follow-up visits and health guidance after discharge.

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Zearalenone (ZEN) is a widespread estrogenic mycotoxin that poses serious health risks to both humans and animals through the contamination of cereals and feeds. In this study, a novel strain X13 was isolated from volcanic rock soil and demonstrated the unique ability to utilize ZEN as the sole carbon source for growth and metabolism. Under optimized conditions (37 °C, pH 8.

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Quantifying the contribution of microbial necromass to soil organic carbon (SOC) has been a hot topic in the past decade, offering critical insights into soil carbon sequestration mechanisms. Amino sugars (AS) are widely used biomarkers for estimating microbial necromass in soils, with the ratios of AS to microbial necromass carbon (MNC) serving as conversion factors to derive MNC from AS measurement. Because AS decomposes more slowly than bulk necromass and persists longer in soil, the ratio of AS to microbial necromass should exceed the AS to biomass ratio in living microbes.

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Three Gram-stain-negative, aerobic, rod-shaped bacterial strains, FR7-31, FR7-34 and HH7-4, were isolated from sediment samples of the Fenhe River basin, China. The 16S rRNA gene sequence analysis revealed that strain FR7-31 shares 99.7% and 99.

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Efficient detoxification is a key factor for the survival of pests exposed to insecticides. UDP-glycosyltransferase (UGT) is a superfamily of phase II detoxifying enzymes, which plays an important role in xenobiotics metabolism including insecticides. As a key post-transcriptional regulator, microRNA (miRNA) has been shown to regulate insecticide resistance by modulating the expression of detoxification enzyme-encoding genes in insects.

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Objectives: While elevated levels of albuminuria beyond 30 mg/g are linked to adverse outcomes, recent studies have revealed an increased risk of chronic kidney disease (CKD) progression and cardiovascular events within the normoalbuminuric range (urinary albumin-to-creatinine ratio, UACR < 30 mg/g). This study aims to examine metabolite levels and inflammatory markers among CKD patients in the normal albuminuria groups.

Methods: We recruited 24 patients diagnosed with CKD exhibiting normoalbuminuria from The Kidney Precision Medicine Project (KPMP).

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Zearalenone (ZEN), a mycotoxin produced by species, is widely distributed and poses significant health risks to both animals and humans due to its toxic effects. In this study, a MF3, exhibiting high ZEN degradation capacity, was identified through comprehensive morphological, physicochemical, 16S rRNA gene sequencing, and whole-genome sequencing analyses. Strain MF3 reached its peak ZEN degradation rate in BHI medium (pH 7, 30°C), with > 90% efficiency maintained across 24-72 h, 1-5% inoculum, and 10-40 μg/mL ZEN.

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This case report details the perioperative management of a 27-year-old male patient with AIDS and a rare giant retroperitoneal calcifying fibrous tumor. The tumor's surgical removal posed high risk due to its proximity to vital structures and the patient's human immunodeficiency virus infection. The report highlights the importance of multidisciplinary collaboration in managing such complex cases.

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Constructing advanced semiconductor nanoreactors is an effective route to boost the efficient photocatalytic conversion of biomasses to high-value-added products. Herein, single-atom anchored flower-like mesoporous TiO nanoreactors with tunable anatase-rutile crystalline phases are prepared via a micelle-interface confined co-assembly strategy (Ru/A&R-TNs). This approach not only facilitates the introduction of various monatomic/diatomic (e.

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DeepPredict is a freely accessible web server that integrates Porter6 and PaleAle6, two state-of-the-art deep learning models designed for protein secondary structure prediction (PSSP) and relative solvent accessibility (RSA) prediction, respectively. Built on an advanced deep learning framework, DeepPredict leverages pre-trained protein language models (PLMs), specifically ESM-2, to eliminate the need for multiple sequence alignments (MSAs), enabling rapid and accurate predictions. Compared to existing methods, DeepPredict outperforms in both PSSP and RSA prediction tasks, delivering state-of-the-art performance.

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With the rapid process of urbanization at a global scale, university campuses have been viewed as important urban green spaces for biodiversity conservation. However, little is known about the role of university campuses in protecting ecological specialists, the species usually vulnerable to anthropogenic disturbance. We assessed the associations between several ecological variates and ecological specialization of bird communities across 198 Chinese university campuses.

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() is a significant traditional Chinese medicine that has been used to treat hiccups, vomiting, nausea, amenorrhea, chronic dysentery, larynx arthralgia, lumbago, and inflammatory diseases in Asia for a long history. Although the chemical composition of has been reported, no thorough review of has been published. Therefore, the present study aimed to comprehensively analyze the ethnobotanical use, phytochemistry, pharmacology, and toxicity of .

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The accurate prediction of protein structures remains a cornerstone challenge in structural bioinformatics, essential for understanding the intricate relationship between protein sequence, structure, and function. Recent advancements in Machine Learning (ML) and Deep Learning (DL) have revolutionized this field, offering innovative approaches to tackle one- dimensional (1D) protein structure annotations, including secondary structure, solvent accessibility, and intrinsic disorder. This review highlights the evolution of predictive methodologies, from early machine learning models to sophisticated deep learning frameworks that integrate sequence embeddings and pretrained language models.

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Background: Perioperative management and lung function recovery are vital for lung cancer patients. We conducted an open-label, single-center, noninferiority, randomized controlled trial in China to evaluate the efficacy of digital therapeutic (DTx)-assisted management vs. multidisciplinary management (MM) in the perioperative management of patients with lung cancer.

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Intrinsically disordered proteins (IDPs) and their intrinsically disordered regions (IDRs) lack stable three-dimensional structures, posing significant challenges for computational prediction. This study introduces PUNCH2 and PUNCH2-light, advanced predictors designed to address these challenges through curated datasets, innovative feature extraction, and optimized neural architectures. By integrating experimental datasets from PDB (PDB_missing) and fully disordered sequences from DisProt (DisProt_FD), we enhanced model performance and robustness.

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PUNCH is a freely accessible web server designed for the rapid and accurate prediction of intrinsically disordered regions (IDRs) in protein sequences. Built on a high-performance computational framework, PUNCH web server which built on PUNCH2-Light predictor, combines speed with predictive accuracy, offering users a streamlined interface for generating predictions from sequence input. Validated against the CAID2 benchmarking datasets, PUNCH web server demonstrates competitive performance in detecting IDRs across diverse protein sequences.

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Background: To date, the non-viral vector Chimeric Antigen Receptor (CAR) T cell preparation platform, exemplified by transposons, has demonstrated significant potential in tumor immunotherapy and yielded positive results in multiple clinical trials. Nonetheless, non-methylated CpG sequences within plasmid DNA can elicit an inflammatory response via Toll-like receptor 9 (TLR9) during CAR-T cell preparation, adversely affecting transgene expression. Additionally, de novo DNA methylation programs promote T cell exhaustion, which poses a significant limitation for CAR-T cell therapy applications.

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Purpose: Breast cancer patients undergoing breast-conserving surgery may require a second operation if positive margins persist but current intraoperative methodologies often lack real-time and comprehensive assessments of tissue margins. This study addresses this critical gap by introducing a novel approach to enhance margin assessment in breast surgery.

Methods: A total of 252 fresh tissue blocks from 199 patients with different types of breast lesions were scanned with a customized swept-source optical coherence tomography (SS-OCT) system, and the OCT features of normal, benign, and malignant breast tissues, were systematically analyzed.

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Background: Intestinal microbiota has a role in early life maturation including maturation of intestinal immune function. However, the interaction of the TLR4 with colonizing bacteria in intestinal development is incompletely understood.

Methods: An established human immature small intestinal cell line, human fetal intestinal organoids, and wild-type (WT) and TLR4 gene knockout (TLR4 ) neonatal mice were used to test the synergism between the innate immune receptor TLR4 and postbiotics from Bifidobacteria longum subsp.

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Background: Neuregulin (NRG) family is involved in energy metabolism, among which NRG1 is a neuregulin proved to play a protective role in MAFLD cells. But the presice echanism has not been fully illustrated. This study aimed to investigate the role of NRG1 via the ERK/SIRT1 signaling in the pathogenesis of MAFLD.

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Predicting the relative solvent accessibility (RSA) of a protein is critical to understanding its 3D structure and biological function. RSA prediction, especially when homology transfer cannot provide information about a protein's structure, is a significant step toward addressing the protein structure prediction challenge. Today, deep learning is arguably the most powerful method for predicting RSA and other structural features of proteins.

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Accurately predicting protein secondary structure (PSSP) is crucial for understanding protein function, which is foundational to advancements in drug development, disease treatment, and biotechnology. Researchers gain critical insights into protein folding and function within cells by predicting protein secondary structures. The advent of deep learning models, capable of processing complex sequence data and identifying meaningful patterns, offer substantial potential to enhance the accuracy and efficiency of protein structure predictions.

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Article Synopsis
  • Traditional cancer treatments often harm the body and lead to new health issues, prompting the need for multimodal combination therapies for better effectiveness.
  • The study introduces a new smart nanomaterial, RM-Cu/P, which uses a mesoporous polydopamine core and RBC membranes to deliver the chemotherapy drug doxorubicin (DOX) while enabling combined therapies like photothermal and chemodynamic treatment.
  • The RM-Cu/P@DOX nanoparticles showed reduced toxicity, enhanced targeting and circulation, and significantly improved antitumor effects through multiple stimulation responses compared to standard monotherapy.
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