GH-UNet: group-wise hybrid convolution-VIT for robust medical image segmentation.

Medical image segmentation is vital for accurate diagnosis. While U-Net-based models are effective, they struggle to capture long-range dependencies in complex anatomy. We propose GH-UNet, a Group-wise Hybrid Convolution-ViT model within the U-Net framework, to address this limitation.

Steps towards overcoming challenges in clinical practice at 1.5T MR-Linac for lung cancer adaptive radiotherapy.

Background: The MR-guided adaptive radiotherapy (MRgART) workflow at the 1.5 T Unity MR-Linac relies on synthetic CT (sCT) generated through bulk density assignment. Although sCT-based dose calculations are the standard approach, it is well known that their accuracy can be compromised in lung tumors due to the high dose gradients surrounding the targets.

In Situ Measurements of Dark Photon Dark Matter Using Parker Solar Probe: Going beyond the Radio Window.

Dark photon dark matter (DPDM) emerges as a compelling candidate for ultralight bosonic dark matter, detectable through resonant conversion into photons within a plasma environment. This Letter employs in situ measurements from the Parker Solar Probe (PSP), the first spacecraft to venture into the solar corona, to probe for DPDM signatures. The PSP in situ measurements go beyond the traditional radio window, spanning frequencies between about 10 kHz and 20 MHz, a challenging range inaccessible to Earth-based radio astronomy.

Dynorphin modulates reward-seeking actions through a pallido-amygdala cholinergic circuit.

The endogenous opioid peptide dynorphin and its receptor κ-opioid receptor (KOR) have been implicated in divergent behaviors, but the underlying mechanisms remain elusive. Here, we show that dynorphin released from nucleus accumbens dynorphinergic neurons exerts powerful modulation over a ventral pallidum (VP) disinhibitory circuit, thereby controlling cholinergic transmission to the amygdala and reward-seeking behavior in mice. On one hand, dynorphin acts postsynaptically via KORs on VP GABAergic neurons to promote disinhibition of cholinergic neurons, which release acetylcholine into the amygdala to facilitate learning and invigorate actions.

A Mannosylated peptidyl lipid CManDA doped into cytidinyl/cationic lipids efficiently delivers siG12Ss to lung cancer in vivo.

Gene therapy has attracted widespread attention in recent years, and one of the important delivery systems is the LNP. However, many LNPs have potential toxicity and accumulate in the liver. Here, we designed and synthesized a Gemini-type mannosylated peptidyl lipid called CManDA(M), which, in combination with the cytidinyl lipid DNCA(D) and the peptidyl lipid CLD(C) (D/50C/50M), could transfect siRNA (siG12S) into A549 cells to target and silence the KRAS gene.

AnomalGRN: deciphering single-cell gene regulation network with graph anomaly detection.

Background: Single-cell RNA sequencing (scRNA-seq) is now essential for cellular-level gene expression studies and deciphering complex gene regulatory mechanisms. Deep learning methods, when combined with scRNA-seq technology, transform gene regulation research into graph link prediction tasks. However, these methods struggle to mitigate the impact of noisy data in gene regulatory networks (GRNs) and address the significant imbalance between positive and negative links.

Medical image segmentation network based on a multisize convolutional kernel association strategy.

Background: Medical image segmentation plays a crucial role in clinical diagnosis and treatment planning by extracting essential information from tissue images.

Purpose: This research aims to address limitations in current medical image segmentation models by proposing a new CKASnet model that enhances adaptability and efficiency while maintaining segmentation accuracy.

Methods: The CKASnet model integrates a novel convolutional kernel association strategy (CKAS), which modifies and updates convolutional kernels to improve their receptive fields and adaptability.

Autologous P63+ lung progenitor cell transplantation in idiopathic pulmonary fibrosis: a phase 1 clinical trial.

Background: In idiopathic pulmonary fibrosis (IPF) patients, alveolar architectures are lost and gas transfer function would decline, which cannot be rescued by conventional anti-fibrotic therapy. P63+ lung basal progenitor cells are reported to have potential to repair damaged lung epithelium in animal models, which need further investigation in clinical trials.

Methods: We cloned and expanded P63+ progenitor cells from IPF patients to manufacture cell product REGEND001, which were further characterized by morphology and single-cell transcriptomic analysis.

A scalable multi-modal learning fruit detection algorithm for dynamic environments.

Introduction: To enhance the detection of litchi fruits in natural scenes, address challenges such as dense occlusion and small target identification, this paper proposes a novel multimodal target detection method, denoted as YOLOv5-Litchi.

Methods: Initially, the Neck layer network of YOLOv5s is simplified by changing its FPN+PAN structure to an FPN structure and increasing the number of detection heads from 3 to 5. Additionally, the detection heads with resolutions of 80 × 80 pixels and 160 × 160 pixels are replaced by TSCD detection heads to enhance the model's ability to detect small targets.

Dual-Domain Self-Supervised Deep Learning with Graph Convolution for Low-Dose Computed Tomography Reconstruction.

X-ray computed tomography (CT) is a commonly used imaging modality in clinical practice. Recent years have seen increasing public concern regarding the ionizing radiation from CT. Low-dose CT (LDCT) has been proven to be effective in reducing patients' radiation exposure, but it results in CT images with low signal-to-noise ratio (SNR), failing to meet the image quality required for diagnosis.

Room-Temperature Organic Spintronic Devices with Wide Range Magnetocurrent Tuning and Multifunctionality via Electro-Optical Compensation Strategy.

In spintronics, devices exhibiting large, widely tunable magnetocurrent (MC) values at room temperature are particularly appealing due to their potential in advanced sensing, data storage, and multifunctional technologies. Organic semiconductors (OSCs), with their rich and unique spin-dependent and (opto-)electronic properties, hold significant promise for realizing such devices. However, current organic devices are constrained by limited design strategies, yielding MC values typically confined to tens of percent, thereby restricting their potential for multifunctional applications.

Cloned airway basal progenitor cells to repair fibrotic lung through re-epithelialization.

Irreversible damage of the lung epithelium in idiopathic pulmonary fibrosis (IPF) patients causes high mortality worldwide, with no lung repair approaches available currently. Here we show that in murine and monkey models, the KRT5 P63 progenitor cells in airway basal layer can enter the alveolar area post fibrotic injury. Aided with an automated culture system, we clone and characterize airway basal progenitor cells from 44 donors with various lung conditions.

A multi-scale information fusion medical image segmentation network based on convolutional kernel coupled updata mechanism.

Medical image segmentation is pivotal in disease diagnosis and treatment. This paper presents a novel network architecture for medical image segmentation, termed TransDLNet, which is engineered to enhance the efficiency of multi-scale information utilization. TransDLNet integrates convolutional neural networks and Transformers, facilitating cross-level multi-scale information fusion for complex medical images.

An Optimized SVR Algorithm for Pulse Pile-Up Correction in Pulse Shape Discrimination.

Pulse pile-up presents a significant challenge in nuclear radiation measurements, particularly in neutron-gamma pulse shape discrimination, as it causes pulse distortion and diminishes identification accuracy. To address this, we propose an optimized Support Vector Regression (SVR) algorithm for correcting pulse pile-up. Initially, the Dung Beetle Optimizer (DBO) and Whale Optimization Algorithm (WOA) are integrated to refine the correction process, with performance evaluated using charge comparison methods (CCM) for pulse shape discrimination.

CK-ATTnet: Medical image segmentation network based on convolutional kernel attention.

The medical image partition model has a wide range of application prospects in medical diagnosis and treatment and has become an important auxiliary method to improve the diagnostic level by medical imaging analysis. After the feature extraction ability of the convolutional neural network (CNN) reached a bottleneck, the form of feature extraction represented by Transformer has made significant achievements in the medical image domain in recent years. However, the structure of Transformer is relatively fixed, the cost of computer resources is large, and it is difficult to adjust the model structure according to the complex medical imaging segmentation task.

Impact of contrast-enhanced CT in the dosimetry of SBRT for liver metastases treated with MR-Linac.

Background: To investigate the impact of using contrast-enhanced computed tomography (CHCT) in the dosimetry of stereotactic body radiation therapy (SBRT) for liver metastases treated with MR-Linac.

Methods: A retrospective study was conducted on 21 liver cancer patients treated with SBRT (50 Gy in 5 fractions) using a 1.5 Tesla Unity MR-Linac.

Dual modules-molecularly imprinted patch-enabled enantioselectively controlled release of racemic drugs for transdermal delivery.

Over 90 % of chiral drugs applied in transdermal drug delivery system (TDDS) are racemates, significantly increasing risks of side effects. Herein, we designed a chiral molecularly imprinted patch (CMIP) that achieved enantioselectively controlled release of S-enantiomers (eutomers) and inhibited the release of R-enantiomers (distomers) for transdermal drug delivery. It is composed of chiral pressure sensitive adhesive (PSA) and molecularly imprinted polymers (MIP), showing better transdermal delivery of S-enantiomers than that of R-enantiomers in vitro (1.

Dynorphin modulates motivation through a pallido-amygdala cholinergic circuit.

The endogenous opioid peptide dynorphin and its receptor κ-opioid receptor (KOR) have been implicated in divergent behaviors, but the underlying mechanisms remain elusive. Here we show that dynorphin released from nucleus accumbens dynorphinergic neurons exerts powerful modulation over a ventral pallidum (VP) disinhibitory circuit, thereby controlling cholinergic transmission to the amygdala and motivational drive in mice. On one hand, dynorphin acts postsynaptically via KORs on local GABAergic neurons in the VP to promote disinhibition of cholinergic neurons, which release acetylcholine into the amygdala to invigorate reward-seeking behaviors.

Assessing the Diagnostic Efficacy of Handgrip Dynamometry and Diaphragmatic Ultrasound in Intensive Care Unit-Acquired Weakness.

Objective: The aim of this study is to examine the diagnostic significance of using handgrip dynamometry and diaphragmatic ultrasound in intensive care unit-acquired weakness (ICU-AW).

Methods: This study included patients who received mechanical ventilation in the ICU at the Fourth Hospital of Hebei Medical University from July to December 2020. We collected comprehensive demographic data and selected conscious patients for muscle strength and ICU-AW assessments.

Fusion of multi-source relationships and topology to infer lncRNA-protein interactions.

Long non-coding RNAs (lncRNAs) are important factors involved in biological regulatory networks. Accurately predicting lncRNA-protein interactions (LPIs) is vital for clarifying lncRNA's functions and pathogenic mechanisms. Existing deep learning models have yet to yield satisfactory results in LPI prediction.

Modeling the Zigzag Curves of Transition Metal Ions' Charge Transition Levels in Crystals.

Predicting the defect levels of transition metal (TM) dopants in the band gap of crystals is critical in determining the charge states of TM dopants and explaining their electronic and optical properties. By analyzing the calculated charge transition levels and the crystal-field strengths of all the 3d-TM ions in several insulators, we demonstrate that the variation trend of the 3d-TM dopants in a crystal is a scaling of the variation of 3d-electron binding energies (ionization potential) of the free TM ions corrected by adding the contribution of the 3d-orbital's crystal-field splitting. We therefore develop a model to predict the relative location of TM ions' defect levels in the band gap from the defect level and crystal-field splitting of a reference TM ion in the host of concern.