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Effect of individual and combined ambient air pollutants exposure on the risk of preeclampsia: a retrospective cohort study in Tangshan, China.

www.ncbi.nlm.nih.gov

Intervention Window for Knee Posttraumatic Osteoarthritis Appears as Early as 1 Week Post Anterior Cruciate Ligament Injury With Macrophage and Osteoclast as Potential Therapeutic Targets in a Rat Model.

To explore the timing of initiating early intervention and potential therapeutic targets for posttraumatic osteoarthritis (PTOA) by characterizing the pathologic trajectory changes in an anterior cruciate ligament transection (ACLT)-induced rat PTOA model.
www.ncbi.nlm.nih.gov

Simultaneous enhanced nitrogen removal and energy recovery in sediment microbial fuel cells using pyrite as anode filler for low C/N ratio wastewater treatment.

Treating low C/N ratio wastewater is challenging because heterotrophic denitrification often suffers from insufficient electron donors. This study investigated the use of conductive pyrite (FeS
www.ncbi.nlm.nih.gov

Dominant determinants of indoor radon concentration and skewed health risk in Al Khums and Al Sahel, Libya.

This study assessed indoor
www.ncbi.nlm.nih.gov

Focussed ultrasound thalamotomy and functional MRI as windows to neural networks underlying essential tremor.

www.ncbi.nlm.nih.gov

Work-related musculoskeletal symptoms across the dental training-practice continuum: a cross-sectional survey.

To estimate the prevalence, frequency, and severity of musculoskeletal symptoms (MSS), and associations with preclinical history, loupe practices, and ergonomic exposures across a dental workforce and training pipeline over a 12-month period.
www.ncbi.nlm.nih.gov

Defining the prognostic performance of multiphase CT-angiography in ischemic stroke patients.

The prognostic performance of multiphase CT-angiography (mCTA) in ischemic stroke patients undergoing endovascular treatment (EVT) in the early and late treatment window remains poorly characterized.
www.ncbi.nlm.nih.gov

Convolutional neural network for real‑time localization of ganglionated plexi from bipolar intracardiac electrograms.

Precise localization of ganglionated plexi (GP) is critical for effective cardioneuroablation, yet current mapping relies on labour‑intensive stimulation and subjective electrogram (EGM) interpretation. Recent advancements in deep learning (DL) have shown the potential to automate and improve outcomes an atrial fibrillation by analyzing EGMs. We aimed to apply DL to raw bipolar EGMs in order to automate GP detection.
www.ncbi.nlm.nih.gov
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