Seasonal effect of PM exposure in patients with COPD: a multicentre panel study.

: Exposure to particulate matter <2.5 μm (PM) is linked to chronic obstructive pulmonary disease (COPD), but most studies lack individual PM measurements. Seasonal variation and their impact on clinical outcomes remain understudied.

Pressure to evade cell-autonomous innate sensing reveals interplay between mitophagy, IFN signaling, and SARS-CoV-2 evolution.

SARS-CoV-2 emerged, and continues to evolve, to efficiently infect humans worldwide. SARS-CoV-2 evades early innate recognition, interferon signaling occurring only in bystander cells. How the virus continues to evolve in the face of innate responses has important consequences, but the pathways involved are incompletely understood.

Active motion can be beneficial for target search with resetting in a thermal environment.

Stochastic resetting has recently emerged as an efficient target-searching strategy in various physical and biological systems. The efficiency of this strategy depends on the type of environmental noise, whether it is thermal or telegraphic (active). While the impact of each noise type on a search process has been investigated separately, their combined effects have not been explored.

Unraveling productivity-enhancing genes in Chinese hamster ovary cells via CRISPR activation screening using recombinase-mediated cassette exchange system.

Chinese hamster ovary (CHO) cells, which are widely used for therapeutic protein production, have been genetically manipulated to enhance productivity. Nearly half of the genes in CHO cells are silenced, which are promising targets for CHO cell engineering. To identify novel gene targets among the silenced genes that can enhance productivity, we established a genome-wide clustered regularly interspaced short palindromic repeats activation (CRISPRa) screening platform for bispecific antibody (bsAb)-producing CHO (CHO-bsAb) cells with 110,979 guide RNAs (gRNAs) targeting 13,812 silenced genes using a virus-free recombinase-mediated cassette exchange-based gRNA integration method.

Unified hierarchical relationship between thermodynamic tradeoff relations.

Recent years have witnessed a surge of discoveries in the studies of thermodynamic inequalities: the thermodynamic uncertainty relation (TUR) and the entropic bound (EB) provide a lower bound on the entropy production (EP) in terms of nonequilibrium currents; the classical speed limit (CSL) expresses the lower bound on the EP using the geometry of probability distributions; the power-efficiency (PE) tradeoff dictates the maximum power achievable for a heat engine given the level of its thermal efficiency. In this study, we show that there exists a unified hierarchical structure encompassing all of these bounds, with the fundamental inequality given by an extension of the TUR (XTUR) that incorporates the most general range of currentlike and state-dependent observables. By selecting more specific observables, the TUR and the EB follow from the XTUR, and the CSL and the PE tradeoff follow from the EB.

Characteristics and sources of potentially toxic elements in road-deposited sediments at the Port of Busan, South Korea: A key contributor to port sediments pollution.

This study investigated the spatial distribution and chemical characteristics of potentially toxic elements (PTEs) in road-deposited sediments (RDS) at the Port of Busan by size fraction. Enrichment factor (EF) values for Zn, Cd, and Sb in fine RDS <250 μm were 52-69, 49-78, and 46-44, respectively, indicating 'extremely high enrichment'. Various statistical analyses, including PCA and PMF models, revealed a strong correlation between pollution levels in RDS <250 μm and vehicle type, identifying non-exhaust emissions (NEE) of vehicles as a primary source of PTEs in RDS from the port.

Segmented readout for Cherenkov time-of-flight positron emission tomography detectors based on bismuth germanate.

Positron emission tomography (PET) is the most sensitive biomedical imaging modality for non-invasively detecting and visualizing positron-emitting radiopharmaceuticals within a subject. In PET, measuring the time-of-flight (TOF) information for each pair of 511-keV annihilation photons improves effective sensitivity but requires high timing resolution. Hybrid materials that emit both scintillation and Cherenkov photons, such as bismuth germanate (BGO), recently offer the potential for more precise timing information from Cherenkov photons while maintaining adequate energy resolution from scintillation photons.

A comprehensive review on Compton camera image reconstruction: from principles to AI innovations.

Compton cameras have emerged as promising tools in biomedical imaging, offering sensitive gamma-ray imaging capabilities for diverse applications. This review paper comprehensively overviews the latest advancements in Compton camera image reconstruction technologies. Beginning with a discussion of the fundamental principles of Compton scattering and its relevance to gamma-ray imaging, the paper explores the key components and design considerations of Compton camera systems.

Strategies for mitigating inter-crystal scattering effects in positron emission tomography: a comprehensive review.

Inter-crystal scattering (ICS) events in Positron Emission Tomography (PET) present challenges affecting system sensitivity and image quality. Understanding the physics and factors influencing ICS occurrence is crucial for developing strategies to mitigate its impact. This review paper explores the physics behind ICS events and their occurrence within PET detectors.

Application of CRISPR/Cas9 Genome Editing to Improve Recombinant Protein Production in CHO Cells.

Genome editing has become an important aspect of Chinese hamster ovary (CHO) cell line engineering for improving the production of recombinant protein therapeutics. Currently, the engineering focus is directed toward expanding product diversity while controlling and improving product quality and yields. In this chapter, we present our protocol for using the genome editing tool Clustered Regularly Interspaced Short Palindromic Repeat (CRISPR)/CRISPR-associated protein 9 (Cas9) to knock out engineering target genes in CHO cells.

Enhanced Timing Performance of Dual-Ended PET Detectors for Brain Imaging Using Dual-Finishing Crystal Approach.

This study presents a novel approach to enhancing the timing performance of dual-ended positron emission tomography (PET) detectors for brain imaging by employing a dual-finishing crystal method. The proposed method integrates both polished and unpolished surfaces within the scintillation crystal block to optimize time-of-flight (TOF) and depth-of-interaction (DOI) resolutions. A dual-finishing detector was constructed using an 8 × 8 LGSO array with a 2 mm pitch, and its performance was compared against fully polished and unpolished crystal blocks.

A Review on Low-Dose Emission Tomography Post-Reconstruction Denoising with Neural Network Approaches.

Low-dose emission tomography (ET) plays a crucial role in medical imaging, enabling the acquisition of functional information for various biological processes while minimizing the patient dose. However, the inherent randomness in the photon counting process is a source of noise which is amplified low-dose ET. This review article provides an overview of existing post-processing techniques, with an emphasis on deep neural network (NN) approaches.

The therapeutic effect of 1-palmitoyl-2-linoleoyl-3-acetyl-rac-glycerol on chemically induced atopic dermatitis.

Atopic dermatitis (AD) is the most common chronic inflammatory skin disease worldwide. However, it is still urgent to develop innovative treatments that can effectively manage refractory patients with unpredictable chronic disease courses. In this study, we evaluated the therapeutic efficacy of 1-palmitoyl-2-linoleoyl-3-acetyl-rac-glycerol (PLAG) as a novel agent for AD treatment using a human-like mouse model of AD.

Federated influencer learning for secure and efficient collaborative learning in realistic medical database environment.

Enhancing deep learning performance requires extensive datasets. Centralized training raises concerns about data ownership and security. Additionally, large models are often unsuitable for hospitals due to their limited resource capacities.

Enhancing bone scan image quality: an improved self-supervised denoising approach.

Bone scans play an important role in skeletal lesion assessment, but gamma cameras exhibit challenges with low sensitivity and high noise levels. Deep learning (DL) has emerged as a promising solution to enhance image quality without increasing radiation exposure or scan time. However, existing self-supervised denoising methods, such as Noise2Noise (N2N), may introduce deviations from the clinical standard in bone scans.

Accurate Automated Quantification of Dopamine Transporter PET Without MRI Using Deep Learning-based Spatial Normalization.

Purpose: Dopamine transporter imaging is crucial for assessing presynaptic dopaminergic neurons in Parkinson's disease (PD) and related parkinsonian disorders. While F-FP-CIT PET offers advantages in spatial resolution and sensitivity over I-β-CIT or I-FP-CIT SPECT imaging, accurate quantification remains essential. This study presents a novel automatic quantification method for F-FP-CIT PET images, utilizing an artificial intelligence (AI)-based robust PET spatial normalization (SN) technology that eliminates the need for anatomical images.

A precise and sustainable doxycycline-inducible cell line development platform for reliable mammalian cell engineering with gain-of-function mutations.

For mammalian synthetic biology research, multiple orthogonal and tunable gene expression systems have been developed, among which the tetracycline (Tet)-inducible system is a key tool for gain-of-function mutations. Precise and long-lasting regulation of genetic circuits is necessary for the effective use of these systems in genetically engineered stable cell lines. However, current cell line development strategies, which depend on either random or site-specific integration along with antibiotic selection, are unpredictable and unsustainable, limiting their widespread use.

Improving F-FDG PET Quantification Through a Spatial Normalization Method.

Quantification of F-FDG PET images is useful for accurate diagnosis and evaluation of various brain diseases, including brain tumors, epilepsy, dementia, and Parkinson disease. However, accurate quantification of F-FDG PET images requires matched 3-dimensional T MRI scans of the same individuals to provide detailed information on brain anatomy. In this paper, we propose a transfer learning approach to adapt a pretrained deep neural network model from amyloid PET to spatially normalize F-FDG PET images without the need for 3-dimensional MRI.

Deciphering Breast Origin in Malignant Effusions: The Diagnostic Utility of an MGP, GATA-3, and TRPS-1 Immunocytochemical Panel.

Introduction: Defining the origin of metastatic cancer is crucial for establishing an optimal treatment strategy, especially when obtaining sufficient tissue from secondary malignancies is limited. While cytological examination is often used in this diagnostic setting, morphologic analysis alone often fails to differentiate metastases derived from the breast from other primaries. The hormone receptor, human epidermal growth factor receptor-2, gross cystic disease fluid protein 15, and mammaglobin immunohistochemistry are often used to diagnose metastatic breast cancer.