Level of empowerment of hospitalized patient in Taiwan clinical practice.

PURPOSE: In the health-care system within hospitals, Taiwanese patients usually play the role of passively cooperating with health-care professionals. Therefore, patients rarely make their own treatment decisions. This study evaluated the level of patient education and patient satisfaction in relation to empowerment level in Taiwan. METHODS: A cross-sectional survey by a self-administered structured questionnaire was carried out with 618 inpatients from the four hospitals. Statistical analyses were then conducted. Analysis of covariance and post-hoc comparison was used to compare differences between the level of patient empowerment, age, and education as covariates in the model. RESULTS: This study found that 21.2% and 35.6% of participants were highly empowered and well empowered, respectively. Years of education is a significant covariate in the counselling domain of patient education. Even after controlling for age and education level, the counselling, answer question and justifying action, providing information scores remain significant for all levels after adjusting for the effects of degree of patient empowerment. Patients with higher empowerment also having more-sufficient patient education, indicating a tendency toward higher patient satisfaction. Patient education and counselling practices in Taiwan's clinical practice could be improved to enhance patient empowerment and ensure health-care systems are person-centred. CONCLUSIONS: To move more toward highly patient empowerment, we suggest that health-care professionals advocate a patient-empowerment approach and to provide more counselling related to patients' illnesses and possible treatments.

BAG-Net: a boundary detection and multiple attention-guided network for liver ultrasound image automatic segmentation in ultrasound guided surgery.

Objective.Automated segmentation of targets in ultrasound (US) images during US-guided liver surgery holds the potential to assist physicians in fast locating critical areas such as blood vessels and lesions. However, this remains a challenging task primarily due to the image quality issues associated with US, including blurred edges and low contrast. In addition, studies specifically targeting liver segmentation are relatively scarce possibly since studying deep abdominal organs under US is difficult. In this paper, we proposed a network named BAG-Net to address these challenges and achieve accurate segmentation of liver targets with varying morphologies, including lesions and blood vessels.Approach.The BAG-Net was designed with a boundary detection module together with a position module to locate the target, and multiple attention-guided modules combined with the depth supervision strategy to enhance detailed segmentation of the target area.Main Results.Our method was compared to other approaches and demonstrated superior performance on two liver US datasets. Specifically, the method achieved 93.9% precision, 91.2% recall, 92.4% Dice coefficient, and 86.2% IoU to segment the liver tumor. Additionally, we evaluated the capability of our network to segment tumors on the breast US dataset (BUSI), where it also achieved excellent results.Significance.Our proposed method was validated to effectively segment liver targets with diverse morphologies, providing suspicious areas for clinicians to identify lesions or other characteristics. In the clinic, the method is anticipated to improve surgical efficiency during US-guided surgery.

A mechanism linking ferroptosis and ferritinophagy in melatonin-related improvement of diabetic brain injury.

Ferroptosis and ferritinophagy play critical roles in various disease contexts. Herein, we observed that ferroptosis and ferritinophagy were induced both in the brains of mice with diabetes mellitus (DM) and neuronal cells after high glucose (HG) treatment, as evidenced by decreases in GPX4, SLC7A11, and ferritin levels, but increases in NCOA4 levels. Interestingly, melatonin administration ameliorated neuronal damage by inhibiting ferroptosis and ferritinophagy both in vivo and in vitro. At the molecular level, we found that not only the ferroptosis inducer p53 but also the ferritinophagy mediator NCOA4 was the potential target of miR-214-3p, which was downregulated by DM status or HG insult, but was increased after melatonin treatment. However, the inhibitory effects of melatonin on ferroptosis and ferritinophagy were blocked by miR-214-3p downregulation. These findings suggest that melatonin is a potential drug for improving diabetic brain damage by inhibiting p53-mediated ferroptosis and NCOA4-mediated ferritinophagy through regulating miR-214-3p in neurons.

Improving Needle Tip Tracking and Detection in Ultrasound-Based Navigation System Using Deep Learning-Enabled Approach.

Ultrasound-guided percutaneous interventions have numerous advantages over traditional techniques. Accurate needle placement in the target anatomy is crucial for successful intervention, and reliable visual information is essential to achieve this. However, previous studies have revealed several challenges, such as the variability in needle echogenicity and the common misalignment of the ultrasound beam and the needle. Advanced techniques have been developed to optimize needle visualization, including hardware-based and image-processing-based methods. This paper proposes a novel strategy of integrating ultrasound-based deep learning approaches into an optical navigation system to enhance needle visualization and improve tip positioning accuracy. Both the tracking and detection algorithms are optimized utilizing optical tracking information. The information is introduced into the tracking network to define the search patch update strategy and form a trajectory reference to correct tracking results. In the detection network, the original image is processed according to the needle insertion position and current position given by the optical localization system to locate a coarse region, and the depth-score criterion is adopted to optimize detection results. Extensive experiments demonstrate that our approach achieves promising tip tracking and detection performance with tip localization errors of 1.11 ± 0.59 mm and 1.17 ± 0.70 mm, respectively. Moreover, we establish a paired dataset consisting of ultrasound images and their corresponding spatial tip coordinates acquired from the optical tracking system and conduct real puncture experiments to verify the effectiveness of the proposed methods. Our approach significantly improves needle visualization and provides physicians with visual guidance for posture adjustment.

Genetic insights into serum cathepsins as diagnostic and therapeutic targets in knee and hip osteoarthritis.

Osteoarthritis (OA) is a chronic disease due to the deterioration of cartilage structure and function, involving the progressive degradation of the cartilage extracellular matrix. Cathepsins, lysosomal cysteine proteases, play pivotal roles in various biological and pathological processes, particularly in protein degradation. Excess cathepsins levels are reported to contribute to the development of OA. However, the causal relationship between the cathepsin family and knee and hip OA remains uncertain. Therefore, this study utilized bidirectional Mendelian Randomization (MR) analyses to explore this causal association. Our results indicated that elevated serum levels of cathepsin O increase the overall risk of knee OA, while increased serum levels of cathepsin H enhance the risk of hip OA. Conversely, the reverse MR analyses did not reveal a reverse causal relationship between them. In summary, OA in different anatomical locations may genetically result from pathological elevations in different serum cathepsin isoforms, which could be utilized as diagnostic and therapeutic targets in clinical practice.