Fruit quality evaluation of different mulberry varieties.

Introduction: The quality of fruits has long been a key focus for breeders, and the development of scientifically sound and reasonable methods for evaluating fruit quality is of great significance in selecting superior cultivars. The mulberry tree, as a plant resource that serves both medicinal and dietary purposes, contains rich nutritional components and various bioactive compounds. These include properties such as immune enhancement, lipid-lowering effects, and anti-tumor activities.

Contrast-enhanced ultrasound-based AI model for multi-classification of focal liver lesions.

Background & Aims: Accurate multi-classification is the prerequisite for reasonable management of focal liver lesions (FLLs). Ultrasound is the common image examination, but lacks accuracy. Contrast enhanced ultrasound (CEUS) offers better performance, but highly relies on experience.

Benefit from public unlabeled data: A Frangi filter-based pretraining network for 3D cerebrovascular segmentation.

Precise cerebrovascular segmentation in Time-of-Flight Magnetic Resonance Angiography (TOF-MRA) data is crucial for computer-aided clinical diagnosis. The sparse distribution of cerebrovascular structures within TOF-MRA images often results in high costs for manual data labeling. Leveraging unlabeled TOF-MRA data can significantly enhance model performance.

GLUT1 as a generic biomarker enables near-infrared fluorescence molecular imaging guided precise intraoperative tumor detection in breast cancer.

Purpose: Precise tumor excision is important but challenging in breast-conserving surgery (BCS). Tumor-specific fluorescence imaging may be used for intraoperative tumor detection and, therefore, to guide precise tumor excision. The aims of this study are to develop a glucose transporter 1 (GLUT1)-targeted near-infrared fluorescence tracer and evaluate its accuracy for breast cancer detection using fresh surgical breast specimens.

[Research progress on the diagnosis of pediatric heart failure].

Heart failure is a complex clinical syndrome and pediatric heart failure (PHF) has a high mortality rate. Early diagnosis is crucial for treatment and management of PHF. In clinical practice, various tests and examinations play a key role in the diagnosis of PHF, including continuously updated biomarkers, echocardiography, and cardiac magnetic resonance imaging.

Deep Equilibrium Unfolding Learning for Noise Estimation and Removal in Optical Molecular Imaging.

In clinical optical molecular imaging, the need for real-time high frame rates and low excitation doses to ensure patient safety inherently increases susceptibility to detection noise. Faced with the challenge of image degradation caused by severe noise, image denoising is essential for mitigating the trade-off between acquisition cost and image quality. However, prevailing deep learning methods exhibit uncontrollable and suboptimal performance with limited interpretability, primarily due to neglecting underlying physical model and frequency information.

DIFLF: A domain-invariant features learning framework for single-source domain generalization in mammogram classification.

Background And Objective: Single-source domain generalization (SSDG) aims to generalize a deep learning (DL) model trained on one source dataset to multiple unseen datasets. This is important for the clinical applications of DL-based models to breast cancer screening, wherein a DL-based model is commonly developed in an institute and then tested in other institutes. One challenge of SSDG is to alleviate the domain shifts using only one domain dataset.

Harmonized technical standard test methods for quality evaluation of medical fluorescence endoscopic imaging systems.

Fluorescence endoscopy technology utilizes a light source of a specific wavelength to excite the fluorescence signals of biological tissues. This capability is extremely valuable for the early detection and precise diagnosis of pathological changes. Identifying a suitable experimental approach and metric for objectively and quantitatively assessing the imaging quality of fluorescence endoscopy is imperative to enhance the image evaluation criteria of fluorescence imaging technology.

Design Principles for Gradient Porous Carbon on Aqueous Zinc-Ion Hybrid Capacitors: A Combined Molecular Dynamic and Machine Learning Study.

Gradient porous carbon has become a potential electrode material for energy storage devices, including the aqueous zinc-ion hybrid capacitor (ZIHC). Compared with the sufficient studies on the fabrication of ZIHCs with high electrochemical performance, there is still lack of in-depth understanding of the underlying mechanisms of gradient porous structure for energy storage, especially the synergistic effect of ultramicropores (<1 nm) and micropores (1-2 nm). Here, we report a design principle for the gradient porous carbon structure used for ZIHC based on the data-mining machine learning (ML) method.

Validation and evaluation of the performance of QIAstat-Dx gastrointestinal panel in pooled stool samples.

In the current study, the analytical sensitivity, analytical specificity, reproducibility, anti-interferences ability, and clinical performance of the QIAstat-Dx Gastrointestinal Panel (GIP) system were evaluated using pooled stool samples. Results showed that the pooled sample test detected the selected ten targets exclusively, with no cross reaction with any other targets of common enteropathogens. The analytical sensitivity of the pooled sample test on QIAstat-Dx GIP system was 10 CFU/ml for Shigella spp.

Perovskite CsCuClxBr3- x Microcrystals: Band Structure, Photochemical Stability, and Photocatalytic Properties.

Although Pb-based metal halide perovskites (MHPs) have excellent photoelectric characteristics, their toxicity remains a limiting factor for their widespread application. In the paper, a series of CsCuClxBr3-x (x = 1, 2, 3) MHP microcrystals were developed and their hydrogen evolution performance in ethanol and HX (X = Cl, Br) was also studied. Among them, CsCuCl3 microcrystals exhibit high hydrogen evolution performance in both HX and ethanol, attributed to their longest average lifetime and suitable band structure.

Improving search strategies in bibliometric studies on machine learning in renal medicine.

This paper evaluated the bibliometric study by Li et al. (Int Urol Nephrol, 2024) on machine learning in renal medicine. Although the study claims to summarize the forefront trends and hotspots in this field, several key issues require further clarification to effectively guide future research.

Encapsulation of fluorescent carbon dots into mesoporous SiO colloidal spheres by surface functionalization-assisted cooperative assembly for high-contrast latent fingerprint development.

Exploiting solid powder fluorescence holds significant potential in diverse domains including medicine and forensics. Conventional fingerprint detection methods often fall short due to low contrast, sensitivity, and high toxicity. To addressing these challenges, we present a novel method for latent fingerprint detection using fluorescent carbon dots (CDs) encapsulated into conventional or mesoporous SiO colloidal spheres (CD@SiO or CDs@m-SiO) through a surface functionalization-assisted cooperative assembly process.

Neovascularization restructuring patterns in diabetic patients with coronary in stent restenosis: an in-vivo optical coherence tomography study.

Patients with diabetes mellitus (DM) have an increased risk of in stent restenosis (ISR). Neovascularization (NV) is considered as a unique pathophysiology factor of ISR in diabetic patients. However, the restructuring patterns of in vivo human coronary NV and their relationship with ISR, especially in diabetic patients remain unclear.

Regulation of intestinal tissue‑resident memory T cells: a potential target for inflammatory bowel disease.

Tissue-resident memory T (TRM) cells are populations which settle down in non-lymphoid tissues instead of returning to secondary lymph organs after the antigen presentation. These cells can provide rapid on-site immune protection as well as long-term tissue damage. It is reported that TRM cells from small intestine and colon exhibited distinctive patterns of cytokine and granzyme expression along with substantial transcriptional and functional heterogeneity.

Comparison of postoperative survival prognosis between early-onset and late-onset esophageal cancer: A Population-based study.

The prognosis of non-distant metastatic early-onset esophageal cancer (EC) patients undergoing surgical treatment remains unclear, this study aims to compare the prognosis of early-onset and late-onset EC. Information on non-distant metastatic EC patients who underwent surgical treatment and were initially diagnosed between 2004 and 2015 was collected from the Surveillance, Epidemiology, and End Results (SEER) database. Propensity score matching (PSM) was used to balance the baseline differences between early-onset and late-onset EC patients.

CXCR4-targeted sensitive magnetic particle imaging for abdominal aortic aneurysm early detection and prognosis evaluation by recognizing total inflammatory cells.

Background: The maximum aortic diameter remains the diagnostic criteria and the indicator for prognosis prediction of abdominal aortic aneurysms (AAA). An additional imaging modality is currently needed to help evaluate the prognosis of AAA as well as early detection of AAA formation. This study evaluated the most effective inflammatory markers for AAA using single-cell sequencing and, from these, developed probes to facilitate in vivo multimodal imaging of AAA inflammation.

Role of stimulated by retinoic acid 6 in 46 children of coarctation of the aorta.

(1) ObjectiveCoarctation of the aorta (CoA) is a complex congenital heart disease. Research on differential genes in patients with CoA and other groups of aortas and investigating the pathogenesis of aorta coarctation is essential for prevention and diagnosis. This study was conducted between January 2019 and December 2021.

Automatic jawbone structure segmentation on dental CBCT images via deep learning.

Objectives: This study developed and evaluated a two-stage deep learning-based system for automatic segmentation of mandibular cortical bone, mandibular cancellous bone, maxillary cortical bone and maxillary cancellous bone on cone beam computed tomography (CBCT) images.

Materials And Methods: A dataset containing 155 CBCT scans acquired with different parameters was obtained. A two-stage deep learning-based system was developed for automatically segmenting jawbone structures.

Improvement of discharge properties for aqueous magnesium-air batteries via a multi-functional and universal electrolyte additive.

Aqueous magnesium-air batteries exhibit significant promise for energy storage because of their superior discharge efficiency, safety features, and affordability. Nonetheless, severe anode self-corrosion and discharge product accumulation can cause the actual discharge performance to be lower than the theoretical value. In this study, glucuronolactone (GLD), an additive with the ability to complex Mg, is utilized to construct a new solvated sheath and to reconfigure the hydrogen-bonding network to reduce the activity of free water.

Safety evaluation of alpha-glycerylphosphorylcholine as a novel food.

To evaluate the safety of alpha-glycerylphosphorylcholine (α-GPC) as a novel food, the study of acute oral toxicity, subchronic toxicity, teratogenic toxicity and genotoxicity were conducted. In acute oral toxicity, no toxic effects were observed in rats of both genders administrated 10.0 g/kg BW α-GPC.