integrative-analysis-targeted-genomic-profiling-immune-cell

Integrative Analysis of Targeted Genomic Profiling and Immune Cell Infiltration in the Prognosis of Lung Adenocarcinoma

The prognosis of lung adenocarcinoma (LUAD) is traditionally evaluated via tumor-node-metastasis (TNM) staging, which does not account for the ...

Yan'an Hospital Affiliated to Kunming Medical University

Kunming Yan'an Hospital

Yunnan Key Laboratory of Tumor Immunological Prevention and Control

Microproteins, prevalent across all kingdoms of life, play a crucial role in cell physiology and human health. Although global gene transcription is widely explored and abundantly available, our understanding of microprotein functions using transcriptome data is still limited. To mitigate this problem, we present a database, Mip-mining ( https://weilab.sjtu.edu.cn/mipmining/ ), underpinned by high-quality RNA-sequencing data exclusively aimed at analyzing microprotein functions. The Mip-mining hosts 336 sets of high-quality transcriptome data from 8626 samples and nine representative living organisms, including microorganisms, plants, animals, and humans, in our Mip-mining database. Our database specifically provides a focus on a range of diseases and environmental stress conditions, taking into account chemical, physical, biological, and diseases-related stresses. Comparatively, our platform enables customized analysis by inputting desired data sets with self-determined cutoff values. The practicality of Mip-mining is demonstrated by identifying essential microproteins in different species and revealing the importance of ATP15 in the acetic acid stress tolerance of budding yeast. We believe that Mip-mining will facilitate a greater understanding and application of microproteins in biotechnology. Moreover, it will be beneficial for designing therapeutic strategies under various biological conditions.

Exploring microproteins from various model organisms using the mip-mining database.

The purpose of this study was to examine the hepatic bacterial composition and metabolome characteristics of patients with NAFLD using 16S rDNA sequencing and metabolomics. The results of the study revealed substantial differences in hepatic bacterial composition and metabolites between the NAFLD group and the control group. These differences were used to identify potential biomarkers that could be employed to diagnose NAFLD.

Characterization of the hepatic flora and metabolome in nonalcoholic fatty liver disease.

Tuberous sclerosis complex (TSC) is a multisystem genetic disorder primarily characterized by the development of benign tumors in multiple organs. While cardiovascular involvement is less common than neurological or renal manifestations, it typically presents with cardiac rhabdomyomas (CRs). The co-occurrence of a bicuspid aortic valve (BAV) with TSC is exceedingly rare.

Case Report: Rare cardiovascular characteristics of tuberous sclerosis complex with novel TSC2 variant.

Recent studies have suggested an interplay between conicity index (C-index)-related diabetes risk and lipid burden. It is plausible that the atherogenic index of plasma (AIP), fatty liver, and HbA1c mediate the association between C-index and diabetes risk, though this has not been fully explored. This study explored whether AIP, fatty liver, and HbA1c mediate the relationship between C-index and diabetes risk, as well as their combined effect.

AIP, fatty liver, and HbA1c as modifiers of the C-index and diabetes risk relationship.

In this study, we investigated the therapeutic effects and mechanisms of umbilical cord mesenchymal stem cells (UCMSCs) in diabetic nephropathy (DN) ZDF (FA/FA) rats. The therapeutic effects were assessed by renal function tests, the urinary albumin-creatinine ratio, PAS staining, electron microscopy, and TGF-1 expression in renal tissue. Subsequently, podocyte injury in renal tissue was detected by immunofluorescence staining for podocin. To further explore the underlying mechanism, serum Angptl4 levels were measured, and Angptl4, integrin 3, fibronectin, and podocin levels in renal tissue were analysed by Western blotting. In vitro, podocytes are stimulated with high glucose and then treated with UCMSCs, and podocyte activity and the expression of synaptopodin, Angptl4, and integrin 3 were observed. UCMSC significantly improve renal function, pathological injury, and podocyte injury in the ZDF (FA/FA) rats. Western blot revealed increased expression of Angptl4, integrin 3, and fibronectin in renal tissues of the DN group, and UCMSC treatment significantly downregulated those proteins. However, UCMSC showed no effects on serum Angptl4 concentration. Podocin expression in renal tissues was significantly restored by UCMSC treatment. In vitro, podocyte activity was decreased after high glucose stimulation and improved by UCMSC treatment. UCMSC restored the expression of synaptopodin, and Angptl4 and downstream integrin 3 were also inhibited. Our study suggested that UCMSC therapy could improve renal function and renal pathological changes in ZDF (FA/FA) rats. In addition, inhibition of the Angptl4/integrin 3 pathway is the potential mechanism by which UCMSC attenuates podocyte injury in the DN model.

Umbilical Cord Mesenchymal Stem Cells Attenuate Podocyte Injury in Diabetic Nephropathy Rats by Inhibiting Angpltl4/Integrin 3 in the Glomerulus.

[This corrects the article DOI: 10.3389/fmicb.2024.1528258.].

Corrigendum: Characterization of the hepatic flora and metabolome in nonalcoholic fatty liver disease.

Alzheimer's disease (AD) etiology is complex, influenced by demographic risk factors such as age, sex, and educational level, alongside multi-omics factors derived from genomics, transcriptomics, and epigenomics. Advancements in multi-omics technology present both challenges and opportunities for AD diagnosis, enabling a more comprehensive understanding of the complex interactions among contributing factors, with the goal of improving diagnostic accuracy. To address this challenge, we propose a novel feature fusion approach in this study, AD-GCN, which integrates multi-omics data and their interaction networks to achieve more precise diagnosis and analysis of AD. In this study, we applied polygenic risk score and random forest algorithms for feature selection on genetic variation and methylation data. We then developed an AD-GCN for both multi-omics and single-omics classification tasks and compared its performance with that of machine learning ensemble methods. The experimental results demonstrated that multi-omics classification significantly outperformed single-omics classification, with AD-GCN surpassing the machine-learning ensembles. These findings highlight AD-GCN's strong potential to enhance AD diagnosis and improve accuracy in differentiating disease stages by integrating interactions across omics data, laying a solid foundation for the development of more precise and personalized AD diagnostic models.

AD-GCN: A novel graph convolutional network integrating multi-omics data for enhanced Alzheimer's disease diagnosis.

The complex pathophysiology and diverse manifestations of esophageal disorders pose challenges in clinical practice, particularly in achieving accurate early diagnosis and risk stratification. While traditional approaches rely heavily on subjective interpretations and variable expertise, machine learning (ML) has emerged as a transformative tool in healthcare. We conducted a comprehensive review of published literature on ML applications in esophageal diseases, analyzing technical approaches, validation methods, and clinical outcomes. ML demonstrates superior performance: In gastroesophageal reflux disease, ML models achieve 80%-90% accuracy in potential of hydrogen-impedance analysis and endoscopic grading; for Barrett's esophagus, ML-based approaches show 88%-95% accuracy in invasive diagnostics and 77%-85% accuracy in non-invasive screening. In esophageal cancer, ML improves early detection and survival prediction by 6%-10% compared to traditional methods. Novel applications in achalasia and esophageal varices demonstrate promising results in automated diagnosis and risk stratification, with accuracy rates exceeding 85%. While challenges persist in data standardization, model interpretability, and clinical integration, emerging solutions in federated learning and explainable artificial intelligence offer promising pathways forward. The continued evolution of these technologies, coupled with rigorous validation and thoughtful implementation, may fundamentally transform our approach to esophageal disease management in the era of precision medicine.

Recent advances in machine learning for precision diagnosis and treatment of esophageal disorders.

Chimeric antigen receptor T (CAR-T) cell therapies have demonstrated significant clinical efficacy in hematological malignancies. However, their application to solid tumors remains substantially limited by multiple challenges, including the risk of off-target effects. Hence, optimizing CAR-T cells for stronger antigen binding is essential.

Investigation on the Anti-Cancer Effects of HER2-Targeted CAR-T Cells Engineered Using the  Transposon System.

Primary amebic meningoencephalitis (PAM) is a rare neurological infectious disease with an extremely high mortality rate. This disease is caused by  invading the brain, and patient infections are usually linked to exposure to contaminated warm freshwater in summer. This case report describes a 56-year-old adult male, who presented with increased intracranial pressure, headache, blurred vision accompanied by dizziness, periorbital edema, fever (38.5 ℃), nausea, vomiting, and chills. The patient had bathed in a wild hot spring one week prior to symptom onset. In this case, we performed Wright-Giemsa staining on the sediment of the patient’s cerebrospinal fluid (CSF) and detected amoebic trophozoites. Through direct wet mount microscopy, we observed live amoebic trophozoites. We further conducted high-throughput pathogen sequencing on the patient’s CSF sediment. The results also confirmed that the infecting pathogen was . Thus, the patient was diagnosed with PAM, and administered combined anti-infection treatment with amphotericin B (1.5 mg/kg·d) and rifampicin (10 mg/kg·d). The patient’s condition remained in critical condition and ultimately died of terminal cerebral hernia. PAM is a rare and difficult to diagnose infectious disease. We achieved rapid diagnosis of PAM through a combination of traditional microbiological microscopic examination and high-throughput sequencing of pathogenic microorganisms. The case report provides valuable experience for the diagnosis and treatment of PAM.

A case report of primary amebic meningoencephalitis in a Chinese adult male.

To investigate ethnic differences inprogression from prediabetes to diabetes in a multi-ethnic community, and develop prediction models for diabetes risk and glycemic progression. This 4.7-year retrospective cohort included 4,726 non-diabetic Han, Yi, and Dai individuals. Cox regression was used to analyze the cumulative incidence of diabetes. Two prediction models were developed and validated: a diabetes risk model and GlycoStep, a model for glycemic progression. Prediabetes was significantly associated with diabetes development (HR = 2.25). Over 4.7 years, the cumulative diabetes incidence was 12.7% in the prediabetes group versus 5.5% in normoglycemic individuals. The Yi had the highest incidence, followed by Han and Dai. The diabetes risk model achieved a C-index of 0.76 and AUCs of 0.65-0.80 over 2-4 years, demonstrating effective predictive performance. Similarly, the GlycoStep model exhibited strong predictive ability (C-index: 0.66; AUC range: 0.68-0.77), with ethnic-specific variations. These findings highlight ethnic disparities in diabetes progression and support individualized prevention strategies in multi-ethnic communities.

Article	Year
Exploring microproteins from various model organisms using the mip-mining database. BMC genomics\| PubMed ID: 37919660	2023
Characterization of the hepatic flora and metabolome in nonalcoholic fatty liver disease. Frontiers in microbiology\| PubMed ID: 39760085	2024
Case Report: Rare cardiovascular characteristics of tuberous sclerosis complex with novel TSC2 variant. Frontiers in cardiovascular medicine\| PubMed ID: 39902087	2024
AIP, fatty liver, and HbA1c as modifiers of the C-index and diabetes risk relationship. Lipids in health and disease\| PubMed ID: 40176079	2025
Umbilical Cord Mesenchymal Stem Cells Attenuate Podocyte Injury in Diabetic Nephropathy Rats by Inhibiting Angpltl4/Integrin 3 in the Glomerulus. Journal of diabetes research\| PubMed ID: 40256245	2025
Corrigendum: Characterization of the hepatic flora and metabolome in nonalcoholic fatty liver disease. Frontiers in microbiology\| PubMed ID: 40336830	2025
AD-GCN: A novel graph convolutional network integrating multi-omics data for enhanced Alzheimer's disease diagnosis. PloS one\| PubMed ID: 40455746	2025
Recent advances in machine learning for precision diagnosis and treatment of esophageal disorders. World journal of gastroenterology\| PubMed ID: 40575335	2025
Investigation on the Anti-Cancer Effects of HER2-Targeted CAR-T Cells Engineered Using the Transposon System. Oncology research\| PubMed ID: 41179290	2025
A case report of primary amebic meningoencephalitis in a Chinese adult male. Parasitology research\| PubMed ID: 41746422	2026
A retrospective cohort study identifies differential diabetes progression among Han, Dai, and Yi groups in Yunnan. iScience\| PubMed ID: 41852728	2026

Yangfan Guo

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