Tether-Directed Electrosynthesis of Bicyclic [60]Fullerene Derivatives Fused with 5-Membered Azacycle and 13-Membered Carbocycle.

Tether-directed electrosynthesis of [60]fullerene derivatives fused with 5-membered azacycle and 13-membered carbocycle, that is, bicyclic 1,4,9,12- and 1,2,4,15-adducts, has been achieved unexpectedly for the first time. The novel bicyclic [60]fullerene derivatives are obtained by the electrochemical reduction of [60]fullerene-fused indolines or lactams and subsequent regioselective cyclization with 2,2″-bis(bromomethyl)-1,1':3',1″-terphenyl. The product structures have been characterized by spectroscopic data and single-crystal X-ray analysis.

Copper-Catalyzed -Heteroannulation of [60]Fullerene with Aryl Sulfonamides and Paraformaldehyde: Synthesis and Functionalization of [60]Fullerene-Fused Imidazolidines.

The Cu(II)-catalyzed -heteroannulation reaction of [60]fullerene (C) with aryl sulfonamides and paraformaldehyde has been disclosed for the synthesis of diverse C-fused imidazolidines, of which one or both of the ArSO moieties could be removed selectively. Further transformations into the unexpected bicyclic 1,2,3,4-adduct and C-fused imidazolidinium iodide salt have also been demonstrated. A plausible reaction mechanism is proposed on the basis of control experiments.

Medical multimodal multitask foundation model for lung cancer screening.

Lung cancer screening (LCS) reduces mortality and involves vast multimodal data such as text, tables, and images. Fully mining such big data requires multitasking; otherwise, occult but important features may be overlooked, adversely affecting clinical management and healthcare quality. Here we propose a medical multimodal-multitask foundation model (M3FM) for three-dimensional low-dose computed tomography (CT) LCS.

Unexpected and divergent mechanosynthesis of furanoid-bridged fullerene dimers CO and CO.

An unexpected, divergent and efficient approach toward furanoid-bridged fullerene dimers CO and CO was established under different solvent-free ball-milling conditions by simply using pristine C as the starting material, water as the oxygen source and FeCl as the mediator. The structures of CO and CO were unambiguously established by single-crystal X-ray crystallography. A plausible reaction mechanism is proposed on the basis of control experiments.

IQAGPT: computed tomography image quality assessment with vision-language and ChatGPT models.

Large language models (LLMs), such as ChatGPT, have demonstrated impressive capabilities in various tasks and attracted increasing interest as a natural language interface across many domains. Recently, large vision-language models (VLMs) that learn rich vision-language correlation from image-text pairs, like BLIP-2 and GPT-4, have been intensively investigated. However, despite these developments, the application of LLMs and VLMs in image quality assessment (IQA), particularly in medical imaging, remains unexplored.

A Denoising Diffusion Probabilistic Model for Metal Artifact Reduction in CT.

The presence of metal objects leads to corrupted CT projection measurements, resulting in metal artifacts in the reconstructed CT images. AI promises to offer improved solutions to estimate missing sinogram data for metal artifact reduction (MAR), as previously shown with convolutional neural networks (CNNs) and generative adversarial networks (GANs). Recently, denoising diffusion probabilistic models (DDPM) have shown great promise in image generation tasks, potentially outperforming GANs.

Synthesis of [60]Fullerene-Fused Lactones via Carboxylic Acid Group-Directed C-H Bond Activation and Further Retro Baeyer-Villiger Reaction.

An efficient palladium-catalyzed reaction of [60]fullerene with benzoic acids via carboxylic acid group-directed C-H bond activation is achieved. The obtained [60]fullerene-fused lactones can undergo a retro Baeyer-Villiger reaction to provide [60]fullerene-fused ketones via apparent reduction in the presence of triflic acid. A representative ketone product obtained by the reduction reaction can be employed as an overcoating layer for the electron-transporting layer in an n-type perovskite solar cell.

Deep Few-view High-resolution Photon-counting Extremity CT at Halved Dose for a Clinical Trial.

The latest X-ray photon-counting computed tomography (PCCT) for extremity allows multi-energy high-resolution (HR) imaging for tissue characterization and material decomposition. However, both radiation dose and imaging speed need improvement for contrast-enhanced and other studies. Despite the success of deep learning methods for 2D few-view reconstruction, applying them to HR volumetric reconstruction of extremity scans for clinical diagnosis has been limited due to GPU memory constraints, training data scarcity, and domain gap issues.

Flipover outperforms dropout in deep learning.

Flipover, an enhanced dropout technique, is introduced to improve the robustness of artificial neural networks. In contrast to dropout, which involves randomly removing certain neurons and their connections, flipover randomly selects neurons and reverts their outputs using a negative multiplier during training. This approach offers stronger regularization than conventional dropout, refining model performance by (1) mitigating overfitting, matching or even exceeding the efficacy of dropout; (2) amplifying robustness to noise; and (3) enhancing resilience against adversarial attacks.

Quad-Net: Quad-Domain Network for CT Metal Artifact Reduction.

Metal implants and other high-density objects in patients introduce severe streaking artifacts in CT images, compromising image quality and diagnostic performance. Although various methods were developed for CT metal artifact reduction over the past decades, including the latest dual-domain deep networks, remaining metal artifacts are still clinically challenging in many cases. Here we extend the state-of-the-art dual-domain deep network approach into a quad-domain counterpart so that all the features in the sinogram, image, and their corresponding Fourier domains are synergized to eliminate metal artifacts optimally without compromising structural subtleties.

LIT-Former: Linking In-Plane and Through-Plane Transformers for Simultaneous CT Image Denoising and Deblurring.

This paper studies 3D low-dose computed tomography (CT) imaging. Although various deep learning methods were developed in this context, typically they focus on 2D images and perform denoising due to low-dose and deblurring for super-resolution separately. Up to date, little work was done for simultaneous in-plane denoising and through-plane deblurring, which is important to obtain high-quality 3D CT images with lower radiation and faster imaging speed.

Electrosynthesis of buckyballs with fused-ring systems from PCBM and its analogue.

[6,6]-Phenyl-C-butyric acid methyl ester (PCBM), a star molecule in the fullerene field, has found wide applications in materials science. Herein, electrosynthesis of buckyballs with fused-ring systems has been achieved through radical α-C-H functionalization of the side-chain ester for both PCBM and its analogue, [6,6]-phenyl-C-propionic acid methyl ester (PCPM), in the presence of a trace amount of oxygen. Two classes of buckyballs with fused bi- and tricyclic carbocycles have been electrochemically synthesized.

Diffusion Prior Regularized Iterative Reconstruction for Low-dose CT.

Computed tomography (CT) involves a patient's exposure to ionizing radiation. To reduce the radiation dose, we can either lower the X-ray photon count or down-sample projection views. However, either of the ways often compromises image quality.

QS-ADN: quasi-supervised artifact disentanglement network for low-dose CT image denoising by local similarity among unpaired data.

Deep learning has been successfully applied to low-dose CT (LDCT) image denoising for reducing potential radiation risk. However, the widely reported supervised LDCT denoising networks require a training set of paired images, which is expensive to obtain and cannot be perfectly simulated. Unsupervised learning utilizes unpaired data and is highly desirable for LDCT denoising.

Translating radiology reports into plain language using ChatGPT and GPT-4 with prompt learning: results, limitations, and potential.

The large language model called ChatGPT has drawn extensively attention because of its human-like expression and reasoning abilities. In this study, we investigate the feasibility of using ChatGPT in experiments on translating radiology reports into plain language for patients and healthcare providers so that they are educated for improved healthcare. Radiology reports from 62 low-dose chest computed tomography lung cancer screening scans and 76 brain magnetic resonance imaging metastases screening scans were collected in the first half of February for this study.

Simultaneous Ring Contraction and Expansion Reaction: Electrosynthesis of Heterocycle-Fused Fulleroids and Photovoltaic Application.

Simultaneous electrochemical ring contraction and expansion reactions remain unexplored to date. Herein, the reductive electrosynthesis of heterocycle-fused fulleroids from fullerotetrahydropyridazines and electrophiles in the presence of a trace amount of oxygen has been achieved with concurrent ring contraction and ring expansion. When trifluoroacetic acid and alkyl bromides are employed as electrophiles, heterocycle-fused fulleroids with a 1,1,2,6-configuration are regioselectively formed.

Noise Suppression With Similarity-Based Self-Supervised Deep Learning.

Image denoising is a prerequisite for downstream tasks in many fields. Low-dose and photon-counting computed tomography (CT) denoising can optimize diagnostic performance at minimized radiation dose. Supervised deep denoising methods are popular but require paired clean or noisy samples that are often unavailable in practice.

Development of metaverse for intelligent healthcare.

The metaverse integrates physical and virtual realities, enabling humans and their avatars to interact in an environment supported by technologies such as high-speed internet, virtual reality, augmented reality, mixed and extended reality, blockchain, digital twins and artificial intelligence (AI), all enriched by effectively unlimited data. The metaverse recently emerged as social media and entertainment platforms, but extension to healthcare could have a profound impact on clinical practice and human health. As a group of academic, industrial, clinical and regulatory researchers, we identify unique opportunities for metaverse approaches in the healthcare domain.

X-ray projection imaging of metal oxide particles inside gingival tissues.

There is increasing recognition that oral health affects overall health and systemic diseases. Nonetheless it remains challenging to rapidly screen patient biopsies for signs of inflammation or the pathogens or foreign materials that elicit the immune response. This is especially true in conditions such as foreign body gingivitis (FBG), where the foreign particles are often difficult to detect.

SPICE: Semantic Pseudo-Labeling for Image Clustering.

The similarity among samples and the discrepancy among clusters are two crucial aspects of image clustering. However, current deep clustering methods suffer from inaccurate estimation of either feature similarity or semantic discrepancy. In this paper, we present a Semantic Pseudo-labeling-based Image ClustEring (SPICE) framework, which divides the clustering network into a feature model for measuring the instance-level similarity and a clustering head for identifying the cluster-level discrepancy.

Palladium-Catalyzed C-H Activation/Cyclization for the Synthesis of [60]Fullerene-Fused Phosphinolactones.

A novel and efficient palladium-catalyzed C-H activation reaction of [60]fullerene with arylphosphinic acids has been developed for the synthesis of [60]fullerene-fused phosphinolactones. A possible reaction mechanism is proposed to explain the generation of the obtained products. A representative product can be further electrochemically transformed into bis-benzylated 1,2- and 1,4-adducts of [60]fullerene.