Establishment of a risk prediction model for residual back pain after percutaneous kyphoplasty in osteoporotic vertebral compression fractures.

Purpose: Severe residual back pain (RBP) after percutaneous kyphoplasty (PKP) significantly impacts postoperative prognosis and quality of life in patients. The aim of this study was to identify the risk factors for RBP in osteoporotic vertebral compression fracture (OVCF) patients after PKP, to establish a risk prediction model, and to validate its effectiveness.

Methods: A case-control study was carried out among OVCF patients, who were assigned to either the training set (these patients were recruited from January 2018 and June 2020) or the validation set (these patients were recruited from July 2020 and December 2020).

Quantitative Evaluation of AI-based Organ Segmentation Across Multiple Anatomical Sites Using Eight Commercial Software Platforms.

Purpose: To evaluate organs-at-risk (OARs) segmentation variability across eight commercial AI-based segmentation software using independent multi-institutional datasets, and to provide recommendations for clinical practices utilizing AI-segmentation.

Methods: 160 planning CT image sets from four anatomical sites: head-and-neck, thorax, abdomen and pelvis were retrospectively pooled from three institutions. Contours for 31 OARs generated by the software were compared to clinical contours using multiple accuracy metrics, including: Dice similarity coefficient (DSC), 95 Percentile of Hausdorff distance (HD95), surface DSC, as well as relative added path length (RAPL) as an efficiency metric.

Spatiotemporal Distribution Patterns and Conservation Priorities of Gymnosperms With Different Leaf Shapes in China Under Climate Change.

Leaf morphology is one of the important indicators for studying the response of plants to climate change. Gymnosperms play a crucial role in maintaining biodiversity and ecosystem stability in China. However, the geographical and altitudinal distribution patterns of gymnosperms with different leaf morphologies in China in response to climate change are not yet fully understood.

Development of a hybrid automated chart checking, data collection, and analysis system.

Purpose: To describe the creation and clinical deployment of an integrated stand-alone hybrid automated chart review platform that is comprised of a database, oncology information system (OIS) interfaces, and a user interface (UI).

Methods: A consensus checklist was developed to homogenize the practices of clinical physics staff and physics residents for all plan types. Critical review of the single checklist's items led to the creation of a new concept, the "plan attribute," which permits specialization of the final checklist based on the characteristics of a particular plan.

The DEC2-SCN2A Axis is Essential for the Anticonvulsant Effects of Cannabidiol by Modulating Neuronal Plasticity.

Impairment of neuronal plasticity is involved in a spectrum of neurological disorders such as epilepsy, yet its regulatory mechanisms remain incompletely understood. Here, it is reported that the basic helix-loop-helix transcription factor DEC2 serves as a pivotal regulator of both neuronal plasticity and epileptogenesis through its repression of sodium voltage-gated channel alpha subunit 2 (SCN2A). Knockdown of DEC2 in hippocampal neurons elevates intrinsic excitability and synaptic transmission, exacerbating seizure susceptibility and severity.

Nomogram for prediction of recurrence in patients with lumbar disc herniation after unilateral biportal endoscopy spinal surgery: a retrospective study.

Objective: This study aimed to construct a nomogram to predict the likelihood of early recurrence in patients with lumbar disc herniation (LDH) following unilateral biportal endoscopic (UBE) surgery.

Methods: A retrospective analysis was conducted on LDH patients who underwent UBE surgery in our department between January 1, 2022, and December 31, 2023. The eligible cohort was randomly divided into training and validation sets in a 7:3 ratio.

Improving the Precision of Deep-Learning-Based Head and Neck Target Auto-Segmentation by Leveraging Radiology Reports Using a Large Language Model.

: The accurate delineation of primary tumors (GTVp) and metastatic lymph nodes (GTVn) in head and neck (HN) cancers is essential for effective radiation treatment planning, yet remains a challenging and laborious task. This study aims to develop a deep-learning-based auto-segmentation (DLAS) model trained on external datasets with false-positive elimination using clinical diagnosis reports. : The DLAS model was trained on a multi-institutional public dataset with 882 cases.

The roles of feedback loops in the Caenorhabditis elegans rhythmic forward locomotion.

Rhythmic behaviors are essential in biological systems, particularly in animal locomotion. The central pattern generator and sensory feedback loop mechanism have been instrumental in explaining many rhythmic locomotion patterns, however, it is insufficient to account for the tunability and robustness of frequency and amplitude in certain oscillatory movements. This suggests the involvement of additional, less understood circuit mechanisms.

Early Temporal Dynamics of Gonadal Development and Sexually Dimorphic Gene Expression During Sex Differentiation in Mandarin Fish (Siniperca chuatsi).

The mandarin fish (Siniperca chuatsi) is a significant freshwater aquaculture species in China, exhibiting sexual dimorphism during growth. However, the cellular and molecular mechanisms underlying early gonadal development and sex differentiation remain unclear. This study traces early gonadal development by examining changes in gonadal histology, germ cell morphologic and distributional changes, and the expression of key signaling molecules.

Simulation-free workflow for lattice radiation therapy using deep learning predicted synthetic computed tomography: A feasibility study.

Purpose: Lattice radiation therapy (LRT) is a form of spatially fractionated radiation therapy that allows increased total dose delivery aiming for improved treatment response without an increase in toxicities, commonly utilized for palliation of bulky tumors. The LRT treatment planning process is complex, while eligible patients often have an urgent need for expedited treatment start. In this study, we aimed to develop a simulation-free workflow for volumetric modulated arc therapy (VMAT)-based LRT planning via deep learning-predicted synthetic CT (sCT) to expedite treatment initiation.

Isorhamnetin Attenuates Isoproterenol-Induced Myocardial Injury by Reducing ENO1 (Alpha-Enolase) in Cardiomyocytes.

The protective effect of isorhamnetin on myocardial injury induced by isoproterenol (ISO) was investigated to identify the key targets and pathways involved, offering potential therapeutic insights for cardiovascular diseases. A myocardial injury model was established through intraperitoneal ISO injection, and the effects of isorhamnetin on apoptosis and oxidative stress in ISO-induced myocardial injury rats were assessed. Additionally, an ISO-induced H9c2 cell injury model was established to evaluate the impact of isorhamnetin on cellular damage.

Uncertainty Co-estimator for Improving Semi-Supervised Medical Image Segmentation.

Recently, combining the strategy of consistency regularization with uncertainty estimation has shown promising performance on semi-supervised medical image segmentation tasks. However, most existing methods estimate the uncertainty solely based on the outputs of a single neural network, which results in imprecise uncertainty estimations and eventually degrades the segmentation performance. In this paper, we propose a novel Uncertainty Co-estimator (UnCo) framework to deal with this problem.

Deep Learning-Based Synthetic CT for Personalized Treatment Modality Selection Between Proton and Photon Therapy in Thoracic Cancer.

: Identifying patients' advantageous radiotherapy modalities prior to CT simulation is challenging. This study aimed to develop a workflow using deep learning (DL)-predicted synthetic CT (sCT) for treatment modality comparison based solely on a diagnostic CT (dCT). : A DL network, U-Net, was trained utilizing 46 thoracic cases from a public database to generate sCT images predicting planning CT (pCT) scans based on the latest dCT, and tested on 15 institutional patients.

Advancements in Radiation Therapy Treatment Workflows for Precision Medicine: A Review and Forward Looking.

The conventional radiation therapy (RT) workflow, standardized over the past 3 decades, comprises 4 key phases: computed tomography (CT) simulation, treatment planning, quality assurance, and treatment delivery. This workflow relies heavily on the acquisition of planning CT scans for accurate 3-dimensional planning and patient positioning. Advancements in on-board 3-dimensional imaging, such as fan-beam or cone-beam CT and magnetic resonance imaging, now offer improved dosimetric accuracy directly or through synthetic CT generation, image deformation, and bulk density override techniques.

Investigating the Distribution Dynamics of the Subgenus in China and Providing Insights into Resources Management Under Future Climate Change.

Rapid climate change has significantly impacted species distribution patterns, necessitating a comprehensive understanding of dominant tree dynamics for effective forest resource management and utilization. The subgenus , a widely distributed taxon in subtropical China, represents an ecologically and economically important group of woody plants valued for both oil production and ornamental purposes. In this study, we employed the BIOMOD2 ensemble modeling framework to investigate the spatial distribution patterns and range dynamics of the subgenus under projected climate change scenarios.

NRG Oncology Assessment of Artificial Intelligence for Automatic Treatment Planning in Radiation Therapy Clinical Trials: Present and Future.

Purpose: Recent advances in artificial intelligence (AI) have showcased the potential of automatic treatment planning for clinical trials involving radiation therapy. This paper offers an overview of the current landscape of AI-based treatment planning, emphasizing its ability to improve plan quality and streamline the planning process.

Methods And Materials: Acknowledging the increasing clinical utilization and promise of these technologies, the NRG Oncology Medical Physcis Subcommittee established a working group to assess the status of AI-based automatic treatment planning for clinical trials, along with its challenges and future directions.

Adaptive signal recognition in mines based on deep learning.

To address the challenges of low recognition accuracy and high system complexity arising from the coexistence of multiple wireless communication technologies and severe signal interference in the complex wireless environment of coal mines, this paper proposes a deep learning-based adaptive signal recognition method. By incorporating grouped residual convolution and channel shuffling techniques, the proposed method significantly reduces the number of model parameters (37% fewer than the original WaveNet) while utilizing dilated causal convolution to capture long-range dependencies in the signal, thereby enhancing the model's ability to discriminate multipath interference features. The introduction of a dynamic channel attention mechanism facilitates adaptive adjustment of feature weights, emphasizing key features while suppressing noise interference, thereby improving recognition accuracy.

Serum hepatitis B core antibody as the prognostic factor for diffuse large B-cell lymphoma.

Diffuse large B-cell lymphoma (DLBCL) is the most common subtype of non-Hodgkin lymphoma (NHL), strongly associated with viral infections. Although the link between hepatitis B virus (HBV) infection and DLBCL is well-documented, effective clinical markers reflecting HBV-associated DLBCL remain scarce. This study aims to identify prognostic indicators for HBV-associated DLBCL through retrospective analysis of the relationship among tissue marker molecules, HBV serum markers, and clinical prognosis in DLBCL patients.

Cadmium exposure and osteoporosis: epidemiological evidence and mechanisms.

Cadmium (Cd) is a toxic heavy metal with a long biological half-life, exerting adverse effects on most tissues and organs in the human body. Inhalation, ingestion, and skin contact are the main ways of exposure to Cd. Bone is one of the target organs of Cd.

Subsequent kilovoltage imaging-based fiducial triangulation for intra-fractional prostate motion monitoring and correction.

Background: Inter-fractional and intra-fractional positioning and motion monitoring based on implanted fiducials through kilovoltage (kV) imaging is a cost-effective approach to enhance intact prostate radiotherapy treatment accuracy. However, comprehensive studies for three-dimensional (3D) position extraction and the corrective action threshold are lacking.

Purpose: To develop and verify a fiducial motion monitoring system with 3D position information based on triggered kV images taken during treatment delivery, and to comprehensively evaluate the recommended thresholds for corrective action during treatment.

Three signalling pathways for iron overload in osteoporosis: a narrative review.

Osteoporosis is a metabolic bone disease characterized by a decrease in the amount of bone tissue per unit volume and changes in bone microstructure, often resulting in bone fragility and increased susceptibility to fracture. Iron plays an important role in the normal physiological activities of human body, and its abnormal metabolism is one of the risk factors of osteoporosis. Iron overload, as an abnormality of iron metabolism, has been reported to be associated with osteoporosis in recent years.

The treatment responses among different inhalation therapies for GOLD group E patients with chronic obstructive pulmonary disease.

Background: The Global Initiative for Chronic Obstructive Lung Disease (GOLD) 2023 revised the combined chronic obstructive pulmonary disease (COPD) assessment, merging groups C and D into group E, and revised the initial inhalation therapy recommendation. We aimed to evaluate the treatment responses among different inhalation therapies in GOLD group E patients stratified by the COPD assessment test (CAT) scores and forced expiratory volume in one-second percentage of predicted (FEV1%pred).

Methods: In this retrospective cohort study, we included patients with COPD registered in the Real World Research of Diagnosis and Treatment of COPD (RealDTC) study between January 2017 and June 2023.