Jove-Journal of Visualized Experiments最新文献

A pediatric left ventricular assist device (LVAD) implantation model was established to simulate pediatric LVAD support and research the mechanism of heart reverse remodeling. Heart failure (HF) is a prevalent global cardiovascular disease. LVAD implantation is an essential method to treat HF. However, existing pediatric LVAD implantation models remain underdeveloped, and the mechanism of LVAD treatment resulting in ventricular reverse remodeling was unclear, especially among children, though there was a lot of research uncovering the possible target. Therefore, it's necessary to find out the mechanism, especially in children. A good model is the foundation for testing the function of a new pediatric LVAD and disclosing the key mechanism. We established a young landrace pig LVAD implantation model, which could be used to assume pediatric LVAD security and effectiveness. After the LVAD was implanted, the LVAD pump maintained stable and uninterrupted blood flow for over 1 month. Besides, the vital signs, including hemodynamics, were stable and within the ideal and normal ranges. This model accurately replicates hemodynamic conditions in clinical patients post-LVAD implantation. It could be used to trace the continuous changes after LVAD implantation. At the same time, it can be used to disclose the reactivity and safety of child LVAD implantation. This protocol is an easy and standard general process to build a uniformization model for child LVAD implantation research.

Nerve repair is crucial for restoring function following axonal injury. However, mature neurons in the central nervous system (CNS) have a limited ability to regenerate their axons after injury due to diminished intrinsic growth capacity and a hostile environment. In contrast, neurons in the peripheral nervous system (PNS) exhibit robust regenerative potential. Among them, adult dorsal root ganglion (DRG) neurons are particularly well-known for their ability to regenerate effectively following peripheral nerve injuries, making them an ideal model for studying the cellular and molecular mechanisms underlying nerve repair. Here, a modified microsuture technique, termed "loop-before-transection," is described for generating a sciatic nerve transection and resuture model in mice, followed by analysis of axon regeneration. Behavioral assessments and muscle reinnervation are also demonstrated to evaluate functional recovery. After sciatic nerve transection and resuture, animals initially exhibit behavioral deficits, but full recovery is typically observed by 30 days post-injury. Applying drugs that promote axonal fusion at the injury site significantly accelerates functional recovery. This model system offers a powerful tool for investigating the mechanisms governing mammalian nerve repair in vivo.

Mechanical ventilation requires intubation and catheterization, which can cause significant damage to the human body, easily exacerbate the patient's pain, and lead to patient-ventilator asynchrony. Therefore, it is necessary to explore a safe, reliable, and more efficient analgesic and sedative measure to reduce the patient's pain stimulation and ensure the orderly implementation of various treatment procedures. In the past, drugs were commonly used for analgesia and sedation in clinical practice. Although the effect was acceptable, long-term and large-scale use might lead to numerous complications or adverse reactions, thus reducing the quality of prognosis. Press-needle therapy, also known as intradermal needle therapy, is a type of acupuncture therapy. It mainly involves embedding needles at acupoints to promote blood circulation and achieve the goal of pain relief. This paper will elaborate on how to use press-needles in a standardized manner to relieve pain in patients undergoing mechanical ventilation.

Stable genetic transformation of plants mediated by Agrobacterium tumefaciens has been a powerful tool for fundamental plant biology research as well as plant biotechnologies that directly impact crop improvement. Simple and effective transformation pipelines, such as the floral-dipping method for Arabidopsis, have drastically advanced large-scale analyses of gene function. However, such a pipeline cannot be applied to plant species that do not undergo sexual reproduction. Rorippa aquatica is an emerging amphibious Brassicaceae model species exhibiting heterophylly, drastic changes of leaf and plant form in terrestrial or underwater environments. R. aquatica exclusively propagates vegetatively. The optimized pipeline presented here provides efficient and reliable Agrobacterium-mediated R. aquatica transformation that does not require sterile tissue culture. Leaf cuttings are briefly immersed in Agrobacterium suspended in transformation buffer containing a binary vector that expresses a visual marker, RUBY, under the constitutive promoter. Subsequently, the inoculants are grown on a water-soaked filter paper in a growth chamber. Then, regenerating plantlets with RUBY red pigmentation are separated and potted in soil. Those initial T1 regenerants (R1-T1) express red sectors. Through cutting out the red sector and repeating the regeneration steps, a large number of transgenic siblings are produced in the next R2-T1 generation, some of which are nearly uniformly red; indicative of RUBY expression. This simple transformation pipeline can be adopted for R. aquatica and possibly other vegetatively propagating plant species to introduce genes of interest to investigate their functions in the adaptation to terrestrial vs. aquatic environments.

This study examines the dilemmas physical education teachers face in reshaping their professional roles within Intelligent Physical Education (IPE) and proposes evidence-based relief strategies. Using a mixed-methods approach, a simple random sampling technique was employed for the quantitative phase, resulting in a usable sample size of N = 126 respondents. Moreover, for the qualitative phase, a purposive sampling strategy was employed, and five physical education teachers were selected for interviews. We integrated quantitative survey data with in-depth qualitative interviews to explore dimensions of job crafting. Our findings reveal significant cognitive, task-based, and relational challenges in adapting to innovative educational environments. Quantitative analysis reveals crucial predictive factors influencing these adaptation challenges, while qualitative data highlight insufficient understanding of AI applications, inadequate institutional support, and deficient technological infrastructure as key barriers. Teachers also expressed concerns about maintaining meaningful teacher-student relationships amid technological transformation. The study demonstrates that teachers' successful adaptation depends on systemic support rather than individual effort alone. We propose comprehensive strategies, including conceptual training, infrastructure development, and ethical guidelines, to facilitate effective job crafting. These findings contribute to understanding educator adaptation in technologically transforming educational landscapes and offer practical guidance for implementing intelligent physical education reforms.

Nonalcoholic fatty liver (NAFL) is usually considered a benign condition; however, once it progresses to non-alcoholic steatohepatitis (NASH), patients face a significantly elevated risk of developing end-stage liver disease. Many studies are attempting to elucidate the molecular mechanism underlying the transition from NAFL to NASH. High-throughput sequencing technologies (such as bulk RNA-seq) have provided researchers with a deeper understanding by examining the transcriptome, revealing the expression of molecules, activation of signaling pathways, and other factors associated with disease progression. There is a wealth of open-source data available for researchers to analyze in order to identify potential targets for disease treatment. However, related research is limited by the lack of an efficient and reliable process for upstream analysis of the transcriptome. Here, a highly reproducible and user-friendly upstream analysis and subsequent related differential gene analysis pipeline is provided to achieve standardized processing and deep parsing of private or public data. The pipeline is divided into four steps: (1) quality control of data; (2) gene mapping; (3) differential gene analysis; and (4) functional analysis. This process aims to uncover the molecular mechanisms of disease transformation and assist researchers in screening potential drug targets and therapeutic approaches through the analysis of Bulk RNA-seq data.

It has been established that repetitive head impacts lead to the accrual of changes in brain function, structure, and chemistry. The helmet is the primary piece of protective equipment for participants in American football. The first helmets were constructed from leather. Plastic helmets with chin straps were developed in the 1950s, but testing standards were not developed until 1973. While those standards resulted in improved padding materials, previous work demonstrated that modern helmets mitigate translational accelerations better than rotational accelerations, especially on a helmet's Rear Aspect. The goal of this study was to detail the methodology used to examine the impact mitigation of football helmets with differing energy dissipation mechanisms, including position-specific helmets. The experiments were integrated within a dimensional analysis framework to yield a technique that makes it possible to simultaneously evaluate translational and rotational accelerations due to quantified impact loads at multiple locations around the helmet. Despite improvements in the overall impact mitigation of one of the helmets tested here, in general, they did not achieve their design goals.

Rotator cuff tears remain one of the most common injuries encountered by shoulder surgeons. Although arthroscopic suture-bridge repair has demonstrated superior biomechanical properties and achieved promising clinical results, tendon retears remain a persistent challenge. To address this issue, we have introduced several refinements to optimize the existing repair techniques. One such refinement is the incorporation of a medial knot in the suture-bridge repair, which can decrease gap formation and enable a watertight repair, thereby improving tendon-bone healing. Another critical modification is the use of a rip-stop configuration in the medial row, which can reduce potential suture cut-out, strengthen the resistance of the suture-tendon interface, and lower the risk of type II retear. Therefore, we propose a novel hybrid repair technique that integrates medial knot-tying suture-bridge repair and rip-stop configuration into a single construct. Additionally, this new repair technique offers the benefit of reducing the number of suture passages and suture anchors required, thereby streamlining the repair process. In summary, this method represents a viable and effective alternative for the treatment of rotator cuff tears and may contribute to reducing the incidence of postoperative retears.

This article introduces the DeciViT-Knee 2025 protocol, a hybrid deep-learning workflow that combines Vision Transformers (ViT-B/16), Bayesian Decision Trees, and a third Fuzzy Inference Layer for the early and interpretable detection of Knee Osteoarthritis (KOA). The process starts by setting up a GPU-enabled environment in PyTorch 2.x and Hugging Face Transformers. Then, it gets radiographic and MRI datasets from the Osteoarthritis Initiative (OAI) and the Multicenter Osteoarthritis Study (MOST). Before the fine-tuned ViT-B/16 model processes the data to obtain 768-dimensional image embeddings, it is curated through contrast enhancement, artefact removal, and normalization. We use Bayesian Decision Trees to analyze these embeddings and provide us with calibrated probabilistic classifications. The fuzzy-inference layer incorporates linguistic reasoning to express diagnostic uncertainty in terms such as low, medium, or high risk. The model's performance surpasses that of the CNN, ResNet-50, and ViT-only baselines, achieving an accuracy of 92.4%, an AUC of 0.964, an F1 score of 0.891, and a Brier score of 0.088. The protocol demonstrates how combining transformer-based global feature extraction, Bayesian probabilistic reasoning, and fuzzy interpretability can create a clearer, reproducible, and clinician-friendly framework for diagnosing musculoskeletal imaging.

Totally implantable venous access ports (TIVAPs) have been proven to be safe and effective and are commonly used in cancer patients. Here, we introduce the entire procedure of CT-guided implantation of a TIVAP through the subclavian vein. A total of 283 nasopharyngeal carcinoma patients, including 215 males and 68 females, underwent TIVAP through the right subclavian vein, with an average age of 46.4 years (range 13-74). One patient experienced a failed right subclavian vein puncture but was able to successfully undergo a left subclavian vein puncture guided by ultrasound. The average operation time was 36.2 min (range 20-90 min), and the length of the catheter was 17.1 cm (range 14-21 cm). There were 3 cases of arterial puncture, 1 case of catheter displacement, 2 cases of hemothorax, 2 cases of pneumothorax, 2 cases of thrombosis, and 2 cases of wound infection. The overall complication rate was 5.3% (15/283). The computed tomography (CT)-guided implantation of a totally implantable venous access port (TIVAP) via the subclavian vein can, therefore, be considered a safe and reliable technique.