Automatic AI tool for opportunistic screening of vertebral compression fractures on chest frontal radiographs: A multicenter study.

Vertebral compression fractures (VCFs) are the most common type of osteoporotic fractures, yet they are often clinically silent and undiagnosed. Chest frontal radiographs (CFRs) are frequently used in clinical practice and a portion of VCFs can be detected through this technology. This study aimed to develop an automatic artificial intelligence (AI) tool using deep learning (DL) model for the opportunistic screening of VCFs from CFRs.

BreasTDLUSeg: A coarse-to-fine framework for segmentation of breast terminal duct lobular units on histopathological whole-slide images.

Automatic segmentation of breast terminal duct lobular units (TDLUs) on histopathological whole-slide images (WSIs) is crucial for the quantitative evaluation of TDLUs in the diagnostic and prognostic analysis of breast cancer. However, TDLU segmentation remains a great challenge due to its highly heterogeneous sizes, structures, and morphologies as well as the small areas on WSIs. In this study, we propose BreasTDLUSeg, an efficient coarse-to-fine two-stage framework based on multi-scale attention to achieve localization and precise segmentation of TDLUs on hematoxylin and eosin (H&E)-stained WSIs.

Massive field-of-view sub-cellular traction force videography enabled by Single-Pixel Optical Tracers (SPOT).

We report a massive field-of-view and high-speed videography platform for measuring the sub-cellular traction forces of more than 10,000 biological cells over 13 mm at 83 frames per second. Our Single-Pixel Optical Tracers (SPOT) tool uses 2-dimensional diffraction gratings embedded into a soft substrate to convert cells' mechanical traction force into optical colors detectable by a video camera. The platform measures the sub-cellular traction forces of diverse cell types, including tightly connected tissue sheets and near isolated cells.

Clinical and economic evaluation of blood culture whole process optimisation in critically ill adult patients with positive blood cultures.

Objectives: Optimising blood culture processing is important to ensure that bloodstream infections are accurately diagnosed while minimising adverse events caused by antibiotic abuse. This study aimed to evaluate the impact of optimised blood culture processes on antibiotic use, clinical outcomes and economics in intensive care unit (ICU) patients with positive blood cultures.

Methods: From March 2020 to October 2021, this microbiology laboratory implemented a series of improvement measures, including the clinical utility of Fastidious Antimicrobial Neutralization (FAN® PLUS) bottles for the BacT/Alert Virtuo blood culture system, optimisation of bottle reception, graded reports and an upgraded laboratory information system.

Pathological Priors Inspired Network for Vertebral Osteophytes Recognition.

Automatic vertebral osteophyte recognition in Digital Radiography is of great importance for the early prediction of degenerative disease but is still a challenge because of the tiny size and high inter-class similarity between normal and osteophyte vertebrae. Meanwhile, common sampling strategies applied in Convolution Neural Network could cause detailed context loss. All of these could lead to an incorrect positioning predicament.

Case report: A toxoplasmic encephalitis in an immunocompromised child detected through metagenomic next-generation sequencing.

Unlabelled: There exist numerous pathogens that are capable of causing infections within the central nervous system (CNS); however, conventional detection and analysis methods prove to be challenging. Clinical diagnosis of CNS infections often depends on clinical characteristics, cerebrospinal fluid (CSF) analysis, imaging, and molecular detection assays. Unfortunately, these methods can be both insensitive and time consuming, which can lead to missed diagnoses and catastrophic outcomes, especially in the case of infrequent diseases.

Massively Concurrent Sub-Cellular Traction Force Videography enabled by Single-Pixel Optical Tracers (SPOTs).

Unlabelled: We report a large field-of-view and high-speed videography platform for measuring the sub-cellular traction forces of more than 10,000 biological cells over 13mm at 83 frames per second. Our Single-Pixel Optical Tracers (SPOT) tool uses 2-dimensional diffraction gratings embedded into a soft substrate to convert cells' mechanical traction stress into optical colors detectable by a video camera. The platform measures the sub-cellular traction forces of diverse cell types, including tightly connected tissue sheets and near isolated cells.

SpineRegNet: Spine Registration Network for volumetric MR and CT image by the joint estimation of an affine-elastic deformation field.

Spine registration for volumetric magnetic resonance (MR) and computed tomography (CT) images plays a significant role in surgical planning and surgical navigation system for the radiofrequency ablation of spine intervertebral discs. The affine transformation of each vertebra and elastic deformation of the intervertebral disc exist at the same time. This situation is a major challenge in spine registration.

PCAN: Pixel-wise classification and attention network for thoracic disease classification and weakly supervised localization.

Automatic chest X-ray (CXR) disease classification has drawn increasing public attention as CXR is widely used in thoracic disease diagnosis. Existing classification networks typically employ a global average pooling layer to produce the final feature for the subsequent classifier. This limits the classification performance owing to the characteristics of lesions in CXR images, including small relative sizes, varied absolute sizes, and different occurrence locations.

DDTNet: A dense dual-task network for tumor-infiltrating lymphocyte detection and segmentation in histopathological images of breast cancer.

The morphological evaluation of tumor-infiltrating lymphocytes (TILs) in hematoxylin and eosin (H& E)-stained histopathological images is the key to breast cancer (BCa) diagnosis, prognosis, and therapeutic response prediction. For now, the qualitative assessment of TILs is carried out by pathologists, and computer-aided automatic lymphocyte measurement is still a great challenge because of the small size and complex distribution of lymphocytes. In this paper, we propose a novel dense dual-task network (DDTNet) to simultaneously achieve automatic TIL detection and segmentation in histopathological images.

Distributed colorimetric interferometer for mapping the pressure distribution in a complex microfluidics network.

We demonstrate a novel platform for mapping the pressure distribution of complex microfluidics networks with high spatial resolution. Our approach utilizes colorimetric interferometers enabled by lossy optical resonant cavities embedded in a silicon substrate. Detection of local pressures in real-time within a fluid network occurs by monitoring a reflected color emanating from each optical cavity.

Intracellular Photothermal Delivery for Suspension Cells Using Sharp Nanoscale Tips in Microwells.

Efficient intracellular delivery of biomolecules into cells that grow in suspension is of great interest for biomedical research, such as for applications in cancer immunotherapy. Although tremendous effort has been expended, it remains challenging for existing transfer platforms to deliver materials efficiently into suspension cells. Here, we demonstrate a high-efficiency photothermal delivery approach for suspension cells using sharp nanoscale metal-coated tips positioned at the edge of microwells, which provide controllable membrane disruption for each cell in an array.

Lift-off cell lithography for cell patterning with clean background.

We developed a highly efficient method for patterning cells by a novel and simple technique called lift-off cell lithography (LCL). Our approach borrows the key concept of lift-off lithography from microfabrication and utilizes a fully biocompatible process to achieve high-throughput, high-efficiency cell patterning with nearly zero background defects across a large surface area. Using LCL, we reproducibly achieved >70% patterning efficiency for both adherent and non-adherent cells with <1% defects in undesired areas.

Liquid Metal-Based Multifunctional Micropipette for 4D Single Cell Manipulation.

A novel manufacturing approach to fabricate liquid metal-based, multifunctional microcapillary pipettes able to provide electrodes with high electrical conductivity for high-frequency electrical stimulation and measurement is proposed. 4D single cell manipulation is realized by applying multifrequency, multiamplitude, and multiphase electrical signals to the microelectrodes near the pipette tip to create 3D dielectrophoretic trap and 1D electrorotation, simultaneously. Functions such as single cell trapping, patterning, transfer, and rotation are accomplished.