Accelerating discovery of bioactive ligands with pharmacophore-informed generative models.

Deep generative models have advanced drug discovery but often generate compounds with limited structural novelty, providing constrained inspiration for medicinal chemists. To address this, we develop TransPharmer, a generative model that integrates ligand-based interpretable pharmacophore fingerprints with a generative pre-training transformer (GPT)-based framework for de novo molecule generation. TransPharmer excels in unconditioned distribution learning, de novo generation, and scaffold elaboration under pharmacophoric constraints.

Cxcl9-deficiency attenuates the progression of post-traumatic osteoarthritis in mice.

Objective: Osteoarthritis (OA) is one of the leading causes of disability in the aging population. While about 10% of the adult population is affected by OA, there is to date no curative treatment and joint replacement surgery remains the only option for treating end-stage OA. Previous studies found elevated levels of the chemokine C-X-C motif ligand 9 (CXCL9) in the synovial fluid of OA knees.

The emerging role of tranexamic acid and its principal target, plasminogen, in skeletal health.

The worldwide burden of skeletal diseases such as osteoporosis, degenerative joint disease and impaired fracture healing is steadily increasing. Tranexamic acid (TXA), a plasminogen inhibitor and anti-fibrinolytic agent, is used to reduce bleeding with high effectiveness and safety in major surgical procedures. With its widespread clinical application, the effects of TXA beyond anti-fibrinolysis have been noticed and prompted renewed interest in its use.

GT-CAM: Game Theory Based Class Activation Map for GCN.

Graph Convolutional Networks (GCN) have shown outstanding performance in skeleton-based behavior recognition. However, their opacity hampers further development. Researches on the explainability of deep learning have provided solutions to this issue, with Class Activation Map (CAM) algorithms being a class of explainable methods.

Increased β-adrenergic signaling promotes fracture healing through callus neovascularization in mice.

Traumatic brain injury (TBI) leads to skeletal changes, including bone loss in the unfractured skeleton, and paradoxically accelerates healing of bone fractures; however, the mechanisms remain unclear. TBI is associated with a hyperadrenergic state characterized by increased norepinephrine release. Here, we identified the β-adrenergic receptor (ADRB2) as a mediator of skeletal changes in response to increased norepinephrine.

BERT-siRNA: siRNA target prediction based on BERT pre-trained interpretable model.

Silencing mRNA through siRNA is vital for RNA interference (RNAi), necessitating accurate computational methods for siRNA selection. Current approaches, relying on machine learning, often face challenges with large data requirements and intricate data preprocessing, leading to reduced accuracy. To address this challenge, we propose a BERT model-based siRNA target gene knockdown efficiency prediction method called BERT-siRNA, which consists of a pre-trained DNA-BERT module and Multilayer Perceptron module.

Transcript-dependent effects of the CALCA gene on the progression of post-traumatic osteoarthritis in mice.

Osteoarthritis represents a chronic degenerative joint disease with exceptional clinical relevance. Polymorphisms of the CALCA gene, giving rise to either a procalcitonin/calcitonin (PCT/CT) or a calcitonin gene-related peptide alpha (αCGRP) transcript by alternative splicing, were reported to be associated with the development of osteoarthritis. The objective of this study was to investigate the role of both PCT/CT and αCGRP transcripts in a mouse model of post-traumatic osteoarthritis (ptOA).

Tranexamic Acid Attenuates the Progression of Posttraumatic Osteoarthritis in Mice.

Background: Posttraumatic osteoarthritis (OA) is a common disorder associated with a high socioeconomic burden, particularly in young, physically active, and working patients. Tranexamic acid (TXA) is commonly used in orthopaedic trauma surgery as an antifibrinolytic agent to control excessive bleeding. Previous studies have reported that TXA modulates inflammation and bone cell function, both of which are dysregulated during posttraumatic OA disease progression.

The selective norepinephrine reuptake inhibitor reboxetine promotes late-stage fracture healing in mice.

Impaired fracture healing is of high clinical relevance, as up to 15% of patients with long-bone fractures display non-unions. Fracture patients also include individuals treated with selective norepinephrine reuptake inhibitors (SNRI). As SNRI were previously shown to negatively affect bone homeostasis, it remained unclear whether patients with SNRI are at risk of impaired bone healing.

Increased beta2-adrenergic signaling is a targetable stimulus essential for bone healing by promoting callus neovascularization.

Traumatic brain injury (TBI) is associated with a hyperadrenergic state and paradoxically causes systemic bone loss while accelerating fracture healing. Here, we identify the beta2-adrenergic receptor (Adrb2) as a central mediator of these skeletal manifestations. While the negative effects of TBI on the unfractured skeleton can be explained by the established impact of Adrb2 signaling on bone formation, Adrb2 promotes neovascularization of the fracture callus under conditions of high sympathetic tone, including TBI and advanced age.

Fracture healing in a mouse model of Hajdu-Cheney-Syndrome with high turnover osteopenia results in decreased biomechanical stability.

Notch signaling regulates cell fate in multiple tissues including the skeleton. Hajdu-Cheney-Syndrome (HCS), caused by gain-of-function mutations in the Notch2 gene, is a rare inherited disease featuring early-onset osteoporosis and increased risk for fractures and non-union. As the impact of Notch2 overactivation on fracture healing is unknown, we studied bone regeneration in mice harboring a human HCS mutation.

Multiple sampling schemes and deep learning improve active learning performance in drug-drug interaction information retrieval analysis from the literature.

Background: Drug-drug interaction (DDI) information retrieval (IR) is an important natural language process (NLP) task from the PubMed literature. For the first time, active learning (AL) is studied in DDI IR analysis. DDI IR analysis from PubMed abstracts faces the challenges of relatively small positive DDI samples among overwhelmingly large negative samples.

Influence of Strengthening Elements and Heat Treatment on Microstructure and Fracture Toughness of NiAl-Cr(Mo)-Based Eutectic Alloy.

Due to their potential improvement of high-temperature properties, the refractory metal hafnium (Hf) and the rare earth holmium (Ho) have attracted much attention. In the present research, NiAl-Cr(Mo) eutectic alloys with different Ho and Hf additions were fabricated by conventional smelting method and heat-treated to study the synergetic influence of strengthening elements and heat treatment. The samples were characterized using XRD, SEM, and TEM, and the three-point bending test was performed to obtain fracture toughness.

Research Progress of Laser Cladding on the Surface of Titanium and Its Alloys.

Titanium (Ti) and its alloys have been widely employed in aeronautical, petrochemical, and medical fields owing to their fascinating advantages in terms of their mechanical properties, corrosion resistance, biocompatibility, and so on. However, Ti and its alloys face many challenges, if they work in severe or more complex environments. The surface is always the origin of failure for Ti and its alloys in workpieces, which influences performance degradation and service life.

In vivo deep-brain 2-photon fluorescent microscopy labeled with near-infrared dyes excited at the 1700 nm window.

2-Photon fluorescence microscopy (2PFM) is an indispensable imaging technology for neuroscience. However, the imaging depth is usually limited to the cortical layer in mouse brain in vivo. Here, we demonstrate deep brain 2PFM in vivo excited at the 1700 nm window, using IR780 and aza-IR780 as fluorescent labels.

Deep-Brain 3- and 4-Photon Fluorescence Imaging of Subcortical Structures Labeled by Quantum Dots Excited at the 2200 nm Window.

Multiphoton microscopy (MPM) is an enabling technology for visualizing deep-brain structures at high spatial resolution . Within the low tissue absorption window, shifting to longer excitation wavelengths reduces tissue scattering and boosts penetration depth. Recently, the 2200 nm excitation window has emerged as the last and longest window suitable for deep-brain MPM.

Predicting microbe-drug associations with structure-enhanced contrastive learning and self-paced negative sampling strategy.

Motivation: Predicting the associations between human microbes and drugs (MDAs) is one critical step in drug development and precision medicine areas. Since discovering these associations through wet experiments is time-consuming and labor-intensive, computational methods have already been an effective way to tackle this problem. Recently, graph contrastive learning (GCL) approaches have shown great advantages in learning the embeddings of nodes from heterogeneous biological graphs (HBGs).

KDM1A drives hepatoblastoma progression by activating the Wnt/β-catenin pathway through inhibition of DKK3 transcription.

This study is to explore the mechanism of KDM1A-regulated hepatoblastoma (HB) development. Cancerous and paracancer tissues of 30 HB patients were collected for detection of KDM1A and DKK3 expression. HuH-6 and HepG2 cells were subjected to assays of cellular activities after treatment with sh-KDM1A, sh-DKK3, and/or XAV-939 (an inhibitor of the Wnt/β-catenin pathway).

Bibliometric and visualized analysis of exercise and osteoporosis from 2002 to 2021.

Background: Bibliometric analysis was designed to investigate a systematic understanding of developments in exercise and osteoporosis research over the past 20 years.

Methods: Relevant publications from the Web of Science Core Collection were downloaded on April 26, 2022. CiteSpace, VOSviewer, and the online bibliometric analysis platform were used to conduct this scientometric study.

An exploratory study of CT radiomics using differential network feature selection for WHO/ISUP grading and progression-free survival prediction of clear cell renal cell carcinoma.

Objectives: To explore the feasibility of predicting the World Health Organization/International Society of Urological Pathology (WHO/ISUP) grade and progression-free survival (PFS) of clear cell renal cell cancer (ccRCC) using the radiomics features (RFs) based on the differential network feature selection (FS) method using the maximum-entropy probability model (MEPM).

Methods: 175 ccRCC patients were divided into a training set (125) and a test set (50). The non-contrast phase (NCP), cortico-medullary phase, nephrographic phase, excretory phase phases, and all-phase WHO/ISUP grade prediction models were constructed based on a new differential network FS method using the MEPM.

ILGBMSH: an interpretable classification model for the shRNA target prediction with ensemble learning algorithm.

Short hairpin RNA (shRNA)-mediated gene silencing is an important technology to achieve RNA interference, in which the design of potent and reliable shRNA molecules plays a crucial role. However, efficient shRNA target selection through biological technology is expensive and time consuming. Hence, it is crucial to develop a more precise and efficient computational method to design potent and reliable shRNA molecules.

Neuropeptide Y and receptors are associated with the pyroptosis of nucleus pulposus in aging and degenerative intervertebral discs of rats.

The neuropeptide Y(NPY) mediates bone metabolism and the degradation of cartilage in the peripheral nervous system. However, its role in the intervertebral disc degeneration (IDD) is less clear and warrant further study. The process of IDD has always been accompanied by inflammatory response and pyroptosis of nucleus pulposus cells (NPCs).

Role of hepatic stellate cells in liver ischemia-reperfusion injury.

Liver ischemia-reperfusion injury (IRI) is a major complication of liver trauma, resection, and transplantation. IRI may lead to liver dysfunction and failure, but effective approach to address it is still lacking. To better understand the cellular and molecular mechanisms of liver IRI, functional roles of numerous cell types, including hepatocytes, Kupffer cells, neutrophils, and sinusoidal endothelial cells, have been intensively studied.

Advances and Challenges in De Novo Drug Design Using Three-Dimensional Deep Generative Models.

A persistent goal for drug design is to generate novel chemical compounds with desirable properties in a labor-, time-, and cost-efficient manner. Deep generative models provide alternative routes to this goal. Numerous model architectures and optimization strategies have been explored in recent years, most of which have been developed to generate two-dimensional molecular structures.