AIMC Topic: Spleen

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Machine learning-assisted decoding of temporal transcriptional dynamics via fluorescent timer.

Nature communications
Investigating the temporal dynamics of gene expression is crucial for understanding gene regulation across various biological processes. Using the Fluorescent Timer protein, the Timer-of-cell-kinetics-and-activity system enables analysis of transcrip...

One-Drop Serum Screening Test to Monitor Tissue Iron Accumulation.

Analytical chemistry
Although iron is an essential element for vital body functions, iron overload (IO) is accompanied by significant cellular damage due to its accumulation within organs. Thus, early diagnosis and accurate identification of the affected organs are criti...

Comprehensive evaluation and application of tissue clearing techniques for 3-D visualization of splenic neural and immune architecture.

American journal of physiology. Cell physiology
As the largest secondary lymphoid organ, the spleen plays a crucial role in initiating and sustaining immune responses against blood-borne pathogens through antigen capture and delivery. It is innervated by both autonomic and sensory nerves, which al...

ShenJiaoLingCao decoction ameliorates cyclophosphamide-induced splenic injury and immunosuppression via the inhibition of MEK/ERK signaling pathway activity and modulation of amino acid metabolism.

Journal of ethnopharmacology
ETHNOPHARMACOLOGICAL RELEVANCE: ShenJiaoLingCao Decoction (SJLCD) is derived from the classic Chinese medicine prescription, which consists of ten kinds of herbs. In China, SJLCD has been used as an immunomodulator in clinical practice for more than ...

Deep learning and radiomics for gastric cancer serosal invasion: automated segmentation and multi-machine learning from two centers.

Journal of cancer research and clinical oncology
OBJECTIVE: The objective of this study is to develop an automated method for segmenting spleen computed tomography (CT) images using a deep learning model. This approach is intended to address the limitations of manual segmentation, which is known to...

The impact of the novel CovBat harmonization method on enhancing radiomics feature stability and machine learning model performance: A multi-center, multi-device study.

European journal of radiology
PURPOSE: This study aims to assess whether the novel CovBat harmonization method can further reduce radiomics feature variability from different imaging devices in multi-center studies and improve machine learning model performance compared to the Co...

Improving spleen segmentation in ultrasound images using a hybrid deep learning framework.

Scientific reports
This paper introduces a novel method for spleen segmentation in ultrasound images, using a two-phase training approach. In the first phase, the SegFormerB0 network is trained to provide an initial segmentation. In the second phase, the network is fur...

Immunohistochemistry-Free Enhanced Histopathology of the Rat Spleen Using Deep Learning.

Toxicologic pathology
Enhanced histopathology of the immune system uses a precise, compartment-specific, and semi-quantitative evaluation of lymphoid organs in toxicology studies. The assessment of lymphocyte populations in tissues is subject to sampling variability and l...

Deep learning reconstruction for accelerated high-resolution upper abdominal MRI improves lesion detection without time penalty.

Diagnostic and interventional imaging
PURPOSE: The purpose of this study was to compare a conventional T1-weighted volumetric interpolated breath-hold examination (VIBE) sequence with a DL-reconstructed accelerated high-resolution VIBE sequence (HR-VIBE) in terms of image quality, lesion...

A novel approach to the cause of death identification-multi-strategy integration of multi-organ FTIR spectroscopy information using machine learning.

Talanta
Identifying the cause of death has always been a major focus and challenge in forensic practice and research. Traditional techniques for determining the causes of death are time-consuming, labor-intensive, have high professional barriers, and are vul...