Molecular Layer Atrophy Mediates the Association of Cumulative Blood Pressure Exposure With Cognitive Decline.

Background: High blood pressure (BP) is a known risk factor for cognitive decline and dementia, but the underlying mechanisms are largely unknown. We investigated the associations of cumulative BP exposure with hippocampal subfield volume and cognitive function and determined whether hippocampal subfield atrophy mediates the association between cumulative BP exposure and cognitive decline.

Methods: Between December 2020 and March 2023, participants were prospectively included from the Kailuan study.

U-shaped network combining dual-stream fusion mamba and redesigned multilayer perceptron for myocardial pathology segmentation.

Background: Cardiac magnetic resonance imaging (CMR) provides critical pathological information, such as scars and edema, which are vital for diagnosing myocardial infarction (MI). However, due to the limited pathological information in single-sequence CMR images and the small size of pathological regions, automatic segmentation of myocardial pathology remains a significant challenge.

Purpose: In the paper, we propose a novel two-stage anatomical-pathological segmentation framework combining Kolmogorov-Arnold Networks (KAN) and Mamba, aiming to effectively segment myocardial pathology in multi-sequence CMR images.

Exploring the role of ligands in gold(I)-catalyzed cyclizations: insights from density functional theory.

This study uses density functional theory (DFT) to examine the gold(I)-catalyzed cascade cyclization of 1,4-dienyl-tethered 2-alkynylbenzaldehydes. It focuses on how different ligands influence regioselectivity and chemoselectivity. A consistent 6-endo-dig cyclization pathway is found, leading to a metal-bound benzopyran intermediate, regardless of the ligand.

DML-MFCM: A multimodal fine-grained classification model based on deep metric learning for Alzheimer's disease diagnosis.

Background: Alzheimer's disease (AD) is a neurodegenerative disorder. There are no drugs and methods for the treatment of AD, but early intervention can delay the deterioration of the disease. Therefore, the early diagnosis of AD and mild cognitive impairment (MCI) is significant.

FDuDoCLNet: Fully dual-domain contrastive learning network for parallel MRI reconstruction.

Magnetic resonance imaging (MRI) is a non-invasive medical imaging technique that is widely used for high-resolution imaging of soft tissues and organs. However, the slow speed of MRI imaging, especially in high-resolution or dynamic scans, makes MRI reconstruction an important research topic. Currently, MRI reconstruction methods based on deep learning (DL) have garnered significant attention, and they improve the reconstruction quality by learning complex image features.

JMJD3 deficiency disturbs dopamine biosynthesis in midbrain and aggravates chronic inflammatory pain.

Midbrain dopamine (mDA) neurons participate in a wide range of brain functions through an intricate regulation of DA biosynthesis. The epigenetic factors and mechanisms in this process are not well understood. Here we report that histone demethylase JMJD3 is a critical regulator for DA biosynthesis in adult mouse mDA neurons.

Prioritization of renewable energy for offshore ship charging stations based on intuitionistic fuzzy GLDS method: A case of China.

Offshore ship charging station (OSCS) projects can help to address the current demand for electric ships for ocean voyages to a large extent. The proper selection of the energy source for power generation is a key part of the OSCS project. To select the optimal renewable energy for OSCS with many difficulties such as the ambiguity of the decision-making environment, the differences in group assessment information, and the conflict and compensation between criteria, this paper proposed a fuzzy multi-criteria decision-making (MCDM) framework.

An investment decision framework for offshore CCUS project under interval-valued fermatean fuzzy environment.

Carbon Capture, Utilization and Storage (CCUS) is an indispensable technology for achieving a net-zero emission society. The offshore CCUS project is still in its infancy. To promote its sustainable development, developing a comprehensive framework for investment decision-making is very crucial.

E-PVT: enhanced position-velocity-time scheduler for computer-controlled optical finishing with comprehensive considerations of dynamics constraints, continuity and efficiency.

Deterministic computer-controlled optical finishing is an essential approach for achieving high-quality optical surfaces. Its determinism and convergence rely heavily on precise and smooth motion control to guide the machine tool over an optical surface to correct residual errors. One widely supported and smooth motion control model is position-velocity-time (PVT), which employs piecewise cubic polynomials to describe positions.

Risk assessment of deep-sea floating offshore wind power projects based on hesitant fuzzy linguistic term set considering trust relationship among experts.

The development of deep-sea floating offshore wind power (FOWP) is the key to fully utilizing water resources to enhance wind resources in the years ahead, and then the project is still in its initial stage, and identifying risks is a crucial step before promoting a significant undertaking. This paper proposes a framework for identifying risks in deep-sea FOWP projects. First, this paper identifies 16 risk criteria and divides them into 5 groups to establish a criteria system.

Effect of total flavonoids of . On neuroinflammation in Alzheimer's disease model amyloid-β (Aβ1-42)-peptide-induced astrocyte activation.

One of the main pathological features noted in Alzheimer's disease (AD) is the presence of plagues of aggregated β-amyloid (Aβ1-42)-peptides. Excess deposition of amyloid-β oligomers (AβO) are known to promote neuroinflammation. Sequentially, following neuroinflammation astrocytes become activated with cellular characteristics to initiate activated astrocytes.

A Spinal MRI Image Segmentation Method Based on Improved Swin-UNet.

As the number of patients increases, physicians are dealing with more and more cases of degenerative spine pathologies on a daily basis. To reduce the workload of healthcare professionals, we propose a modified Swin-UNet network model. Firstly, the Swin Transformer Blocks are improved using a residual post-normalization and scaling cosine attention mechanism, which makes the training process of the model more stable and improves the accuracy.

3D reconstruction for maxillary anterior tooth crown based on shape and pose estimation networks.

Purpose: The design of a maxillary anterior tooth crown is crucial to post-treatment aesthetic appearance. Currently, the design is performed manually or by semi-automatic methods, both of which are time-consuming. As such, automatic methods could improve efficiency, but existing automatic methods ignore the relationships among crowns and are primarily used for occlusal surface reconstruction.

Knowledge and vaccination acceptance toward the human monkeypox among men who have sex with men in China.

Background: MSM individuals are at high risk of monkeypox infection, and judicious use of vaccines can control the outbreak. Therefore, we conducted a national cross-sectional survey to assess the vaccination willingness, associated factors, and related knowledges of monkeypox among MSM individuals in China.

Methods: This anonymous cross-sectional study was conducted in China from July 1 to July 3, 2022, and electronic questionnaires were sent online to MSM individuals of specific institutions.

Texture-less surface reconstruction using shape-based image augmentation.

The development of intelligent Robot-Assisted Minimally Invasive Surgery demands geometric reconstruction from endoscopic images. However, images of human tissue surfaces are commonly texture-less. Obtaining the dense depth map of a texture-less scene is very difficult because traditional feature-based 3D reconstruction methods cannot detect enough features to build dense correspondences for depth computation.

An image-guided hybrid robot system for dental implant surgery.

Purpose: Dental implant surgery is an effective method for remediating the loss of teeth. Robot is expected to increase the accuracy of dental implant surgery. However, most of them are industrial serial robot, with low stiffness and non-unique inverse kinematic solution, which may reduce the success rate and safety of robotic surgery.

Multi-Dimension and Multi-Feature Hybrid Learning Network for Classifying the Sub Pathological Type of Lung Nodules through LDCT.

In order to develop appropriate treatment and rehabilitation plans with regard to different subpathological types (PILs and IAs) of lung nodules, it is important to diagnose them through low-dose spiral computed tomography (LDCT) during routine screening before surgery. Based on the characteristics of different subpathological lung nodules expressed from LDCT images, we propose a multi-dimension and multi-feature hybrid learning neural network in this paper. Our network consists of a 2D network part and a 3D network part.

Chlorine-Incorporation-Induced Formation of the Layered Phase for Antimony-Based Lead-Free Perovskite Solar Cells.

The environmental toxicity of Pb in organic-inorganic hybrid perovskite solar cells remains an issue, which has triggered intense research on seeking alternative Pb-free perovskites for solar applications. Halide perovskites based on group-VA cations of Bi and Sb with the same lone-pair ns state as Pb are promising candidates. Herein, through a joint experimental and theoretical study, we demonstrate that Cl-incorporated methylammonium Sb halide perovskites (CHNH)SbClI show promise as efficient solar absorbers for Pb-free perovskite solar cells.

Enhanced Thermochemical Stability of CHNHPbI Perovskite Films on Zinc Oxides via New Precursors and Surface Engineering.

Hydroxyl groups on the surface of ZnO films lead to the chemical decomposition of CHNHPbI perovskite films during thermal annealing, which limits the application of ZnO as a facile electron-transporting layer (ETL) in perovskite solar cells. In this work, we report a new recipe that leads to substantially reduced hydroxyl groups on the surface of the resulting ZnO films by employing polyethylenimine (PEI) to replace generally used ethanolamine in the precursor solutions. Films derived from the PEI-containing precursors are denoted as P-ZnO and those from the ethanolamine-containing precursors as E-ZnO.