Monoexponential, biexponential, stretched exponential and diffusion kurtosis models of diffusion-weighted imaging: a quantitative differentiation of solitary pulmonary lesion.

Background: Diffusion-weighted imaging (DWI) can be used for quantitative tumor assessment. DWI with different models may show different aspects of tissue characteristics.

Objective: To investigate the diagnostic performance of parameters derived from monoexponential, biexponential, stretched exponential magnetic resonance diffusion weighted imaging (DWI) and diffusion kurtosis imaging (DKI) in differentiating benign from malignant solitary pulmonary lesions (SPLs).

MMD-Net: Image domain multi-material decomposition network for dual-energy CT imaging.

Background: Multi-material decomposition is an interesting topic in dual-energy CT (DECT) imaging; however, the accuracy and performance may be limited using the conventional algorithms.

Purpose: In this work, a novel multi-material decomposition network (MMD-Net) is proposed to improve the multi-material decomposition performance of DECT imaging.

Methods: To achieve dual-energy multi-material decomposition, a deep neural network, named as MMD-Net, is proposed in this work.

Spatiotemporal distribution of neurotoxin β-N-methylamino-L-alanine and 2,4-diaminobutyric acid in offshore aquaculture area of Shandong province, China.

The neurotoxin β-N-methylamino-L-alanine (BMAA) has been widely detected in aquatic environments and got the public's attention due to its potential risk to human neurodegenerative diseases. Three cruises in spring, summer and autumn seasons were carried out in Laizhou Bay (LZB), Sishili Bay (SSLB), Sanggou Bay (SGB), Jiaozhou Bay (JZB) and Haizhou Bay (HZB) in 2023. Results showed that the temporal distribution pattern of BMAA in plankton varied in the survey bays.

Non-invasive multimodal CT deep learning biomarker to predict pathological complete response of non-small cell lung cancer following neoadjuvant immunochemotherapy: a multicenter study.

Objectives: Although neoadjuvant immunochemotherapy has been widely applied in non-small cell lung cancer (NSCLC), predicting treatment response remains a challenge. We used pretreatment multimodal CT to explore deep learning-based immunochemotherapy response image biomarkers.

Methods: This study retrospectively obtained non-contrast enhanced and contrast enhancedbubu CT scans of patients with NSCLC who underwent surgery after receiving neoadjuvant immunochemotherapy at multiple centers between August 2019 and February 2023.

Spatiotemporal distribution of lipophilic shellfish toxins in plankton and shellfish in the offshore regions of Shandong province, China.

Lipophilic shellfish toxins (LSTs) threaten the ecosystem health and seafood safety. To comprehensively investigate the spatiotemporal distribution of common LSTs in phytoplankton, zooplankton and economic shellfish, three cruises were conducted in five typical offshore aquaculture regions of Shandong province, China, including Haizhou Bay, Jiaozhou Bay, Sanggou Bay, Sishili Bay and Laizhou Bay, in spring (March-April), summer (July-August) and autumn (November-December). This study revealed significant variability in the composition and content of LSTs in phytoplankton samples collected from different regions.

Spatial distribution of lipophilic shellfish toxins in seawater and sediment in the Bohai Sea and the Yellow Sea, China.

Lipophilic shellfish toxins (LSTs) are widely distributed in marine environments worldwide, potentially threatening marine ecosystem health and aquaculture safety. In this study, two large-scale cruises were conducted in the Bohai Sea and the Yellow Sea, China, in spring and summer 2023 to clarify the composition, concentration, and spatial distribution of LSTs in the water columns and sediments. Results showed that okadaic acid (OA), dinophysistoxin-1 (DTX1) and/or pectenotoxin-2 (PTX2) were detected in 249 seawater samples collected in spring and summer.

Freehand 3D Ultrasound Imaging Based on Probe-mounted Vision and IMU System.

Objectives: Freehand three-dimensional (3D) ultrasound (US) is of great significance for clinical diagnosis and treatment, it is often achieved with the aid of external devices (optical and/or electromagnetic, etc.) that monitor the location and orientation of the US probe. However, this external monitoring is often impacted by imaging environment such as optical occlusions and/or electromagnetic (EM) interference.

Clinical evaluation of pulmonary quantitative computed tomography parameters for diagnosing eosinophilic chronic obstructive pulmonary disease: Characteristics and diagnostic performance.

Aims: To investigate the characteristics and diagnostic performance of quantitative computed tomography (QCT) parameters in eosinophilic chronic obstructive pulmonary disease (COPD) patients.

Methods: High-resolution CT scans of COPD patients were retrospectively analyzed, and various emphysematous parenchyma measurements, including lung volume (LC), lung mean density (LMD), lung standard deviation (LSD), full-width half maximum (FWHM), and lung relative voxel number (LRVN) were performed. The QCT parameters were compared between eosinophilic and noneosinophilic COPD patients, using a definition of eosinophilic COPD as blood eosinophil values ≥ 300 cells·µL on at least three times.

Predicting brain age using partition modeling strategy and atlas-based attentional enhancement in the Chinese population.

As a biomarker of human brain health during development, brain age is estimated based on subtle differences in brain structure from those under typical developmental. Magnetic resonance imaging (MRI) is a routine diagnostic method in neuroimaging. Brain age prediction based on MRI has been widely studied.

Diffusely Charged Polymeric Zwitterions as Loosely Hydrated Marine Antifouling Coatings.

Polymeric zwitterions exhibit exceptional fouling resistance through the formation of a strongly hydrated surface of immobilized water molecules. While being extensively tested for their performance in biomedical, membrane, and, to a lesser extent, marine environments, few studies have investigated how the molecular design of the zwitterion may enhance its performance. Furthermore, while theories of zwitterion antifouling mechanisms exist for molecular-scale foulant species (e.

Comparative genomics reveals evolutionary drivers of the dietary shift in Hemiptera.

Hemiptera insects exhibit a close relationship to plants and demonstrate a diverse range of dietary preferences, encompassing phytophagy as the predominant feeding habit while a minority engages in carnivorous or haematophagous behaviour. To counteract the challenges posed by phytophagous insects, plants have developed an array of toxic compounds, causing significant evolutionary selection pressure on these insects. In this study, we employed a comparative genomics approach to analyse the expansion and contraction of gene families specific to phytophagous insect lineages, along with their adaptive evolutionary traits, utilising representative species from the Hemiptera order.

Investigation of rare earth-based magnetic nanocomposites for specific enrichment of exosomes from human plasma.

Exosomes, also known as small extracellular vesicles, are widely present in a variety of body fluids (e.g., blood, urine, and saliva).

Highly active antiretroviral therapy-related effects on morphological connectivity in HIV.

Objective: Suboptimal concentration of the antiretroviral drug is insufficient to inhibit HIV destruction on brain structure and function due to the resistance of blood brain barrier. We aimed to investigate highly active antiretroviral therapy (HAART)-related effects on the morphological connectivity in people with HIV (PWH).

Design: Case-control study.

CUDC‑101 is a potential target inhibitor for the EGFR‑overexpression bladder cancer cells.

Bladder cancer is one of the most common urological malignancies worldwide. The molecular mechanism underlying its development is complex, but its carcinogenesis has been proposed to occur with cell proliferation and resistance to apoptosis, driven by the signaling activity of abundant EGFR and receptor tyrosine‑protein kinase erbB‑2. In the present study, T24 bladder cancer cell lines with EGFR‑overexpression were constructed, before the multi‑target inhibitor CUDC‑101 was used to investigate its potential as a targeted therapeutic agent for bladder cancer using chemosensitivity methods.

Development and Validation of a Deep Learning Radiomics Model to Predict High-Risk Pathologic Pulmonary Nodules Using Preoperative Computed Tomography.

Rationale And Objectives: To accurately identify the high-risk pathological factors of pulmonary nodules, our study constructed a model combined with clinical features, radiomics features, and deep transfer learning features to predict high-risk pathological pulmonary nodules.

Materials And Methods: The study cohort consisted of 469 cases of lung adenocarcinoma patients, divided into a training cohort (n = 400) and an external validation cohort (n = 69). We obtained computed tomography (CT) semantic features and clinical characteristics, as well as extracted radiomics and deep transfer learning (DTL) features from the CT images.

Hydration behaviors of nonfouling zwitterionic materials.

Zwitterionic materials have emerged as highly effective ultralow fouling materials for many applications, however the underlying mechanism of fouling resistance remains unclear. Using molecular dynamics simulations and surface-sensitive sum frequency generation vibrational spectroscopy, we studied the hydration behaviors of zwitterionic materials, including trimethylamine--oxide (TMAO) and carboxybetaines of different charge-separation distances, to understand their fouling-resistant mechanism and provide a design principle for improved performance. Our study reveals that the interplay among hydrogen bonding, net charge, and dipole moment is crucial to the fouling-resistant capabilities of zwitterionic materials.

Mutually communicated model based on multi-parametric MRI for automated segmentation and classification of prostate cancer.

Background: Multiparametric magnetic resonance imaging (mp-MRI) is introduced and established as a noninvasive alternative for prostate cancer (PCa) detection and characterization.

Purpose: To develop and evaluate a mutually communicated deep learning segmentation and classification network (MC-DSCN) based on mp-MRI for prostate segmentation and PCa diagnosis.

Methods: The proposed MC-DSCN can transfer mutual information between segmentation and classification components and facilitate each other in a bootstrapping way.

Six first-line tyrosine kinase inhibitors reveal novel inhibition potential for the EGFR S768I mutation.

Lung cancer, the leading cause of cancer-related mortality, is the most commonly diagnosed cancer. Tyrosine kinase inhibitors (TKIs) are considered a drug-targeted therapy for non-small cell lung cancers (NSCLCs) with epidermal growth factor receptor (EGFR) mutations. However, limited data are available involving the activity of EGFR TKIs against rare EGFR mutations.

Defining the sensitivity landscape of EGFR variants to tyrosine kinase inhibitors.

Tyrosine kinase inhibitor (TKI) is a standard treatment for patients with NSCLC harboring constitutively active epidermal growth factor receptor (EGFR) mutations. However, most rare EGFR mutations lack treatment regimens except for the well-studied ones. We constructed two EGFR variant libraries containing substitutions, deletions, or insertions using the saturation mutagenesis method.

Machine learning-based combined nomogram for predicting the risk of pulmonary invasive fungal infection in severely immunocompromised patients.

Background: Early and accurate diagnosis of invasive fungal infection (IFI) is pivotal for the initiation of effective antifungal therapy for patients with hematologic malignancies.

Methods: This retrospective study involved 235 patients with hematologic malignancies and pulmonary infections diagnosed as IFIs (n=118) or bacterial pneumonia (n=117). Patients were randomly divided into training (n=188) and validation (n=47) datasets.