Efficacy of catgut embedding in Baihui (GV20) and Feishu (BL13) and Pishu (BL20) on lung tissue, brain tissue and blood related indexes in rats with allergic rhinitis of lung deficiency type.

OBJECTIVE: To investigate the effects of acupoint catgut embedding for 3 weeks on lung tissue, blood immunoglobulin E (IgE) and interleutin-4 (IL-4), brain tissue microglia x-42 (OX-42) and toll-like receptor-2 (TLR-2) in rats with allergic rhinitis of lung deficiency type. METHODS: Forty-five female Sprague-Dawley rats were randomly divided for two times. The first time, they were randomly divided into model group and blank group (Group C) according to 2:1, and the second time, the model group were randomly divided into model control group (Group B) and intervention treatment group (Group A) according to 1:1. 15 in each group. For Group A and Group B, the lung deficiency model was made by "sulfur-moxa fumigation", and then the allergic rhinitis model was established by "ovalbumin (OVA) sensitization". Then catgut embedding was performed at acupoints in Group A and not in Group B. After 3 weeks, collect lung tissue samples for hematoxylin-eosin staining, then take blood to observe the concentration of IgE and IL-4, and finally take brain tissue to observe the results of OX-42 and TLR-2. RESULTS: IgE level (µg/mL) was (3.11 ± 0.20) in the Group A, (4.19 ± 0.44) in the Group B, and (2.29 ± 0.30) in the Group C (all < 0.001). IL-4 level (pg/mL) was (14.2 ± 0.7) in the Group A, (18.6 ± 2.4) in the Group B, and (11.4 ± 1.2) for the Group C (all < 0.001). The mean OD for OX-42 is (0.1728 ± 0.0016) in the Group A, (0.1810 ± 0.0046) in the Group B and (0.1674 ± 0.0025) in the Group C (all < 0.001). CONCLUSION: Although 3 weeks of acupoint catgut embedding already showed obvious efficacy on rats with allergic rhinitis, the allergic reaction in the body still continued. To achieve further treatment, prolonging the catgut embedding time is necessary.

Application of Deep Learning Techniques for Detection of Pneumothorax in Chest Radiographs.

With the advent of Artificial Intelligence (AI) and even more so recently in the field of Machine Learning (ML), there has been rapid progress across the field. One of the prominent examples is image recognition in the medical category, such as X-ray imaging, Computed Tomography (CT), and Magnetic Resonance Imaging (MRI). It has the potential to alleviate a doctor's heavy workload of sifting through large quantities of images. Due to the rising attention to lung-related diseases, such as pneumothorax and nodules, ML is being incorporated into the field in the hope of alleviating the already strained medical resources. In this study, we proposed a system that can detect pneumothorax diseases reliably. By comparing multiple models and hyperparameter configurations, we recommend a model for hospitals, as its focus on minimizing false positives aligns with the precision required by medical professionals. Through our cooperation with Poh-Ai Hospital, we acquired a total of over 8000 X-ray images, with more than 1000 of them from pneumothorax patients. We hope that by integrating AI systems into the automated process of scanning chest X-ray images with various diseases, more resources will be available in the already strained medical systems. Our proposed system showed that the best model that is used for transfer learning from our dataset performed with an AP of 51.57 and an AP75 of 61.40, with accuracy at 93.89%, a false positive of 1.12%, and a false negative of 4.99%. Based on the feedback from practicing doctors, they are more wary of false positives. For their use case, we recommend another model due to the lower false positive rate and higher accuracy compared with other models, which in our test shows a rate of only 0.88% and 95.68%, demonstrating the feasibility of the research. This promising result showed that it could be utilized in other types of diseases and expand to more hospitals and medical organizations, potentially benefitting more people.

Nightmare Distress as a Risk Factor for Suicide Among Adolescents with Major Depressive Disorder.

Purpose: Nightmare is common and is also independently implicated in suicide risk among the adolescent population. Adolescents with major depressive disorder (MDD) are at an increased risk of suicide. Therefore, comorbid nightmares may amplify suicide risk among this clinical population. This study aimed to explore the effects of nightmares on suicide risk among adolescents with MDD. Patients and Methods: Subjects were 499 outpatients aged 12-18 in four large psychiatric hospitals clinic of China, from January 1 to October 31, 2021. Simultaneously, we matched 499 healthy controls according to gender and age. All participants underwent affective state (depressive and anxiety symptoms) and sleep variable (nightmare frequency/distress, insomnia symptoms, and daytime sleepiness) evaluation as well as MDD diagnoses and determination of suicide risk by a fully structured diagnostic clinical interview. Results: Adolescents with MDD reported a higher incidence of frequent nightmares (at least one night per week) and level of nightmare distress than healthy controls (22.0% vs 6.1%; 28.85 ± 11.92 vs 17.30 ± 5.61). Over half of the patients with suicide risk (51.6%) experienced frequent nightmares compared with approximately one-third of those at a risk for suicide (30.7%). Patients with suicide risk scored scientifically higher on sleep variables, depressive and anxiety symptoms than those without the risk. Further logistic regression analysis indicated that female gender, junior grade, recurrent depressive episode, severe nightmare distress and severe depressive symptoms were independently and significantly associated with suicide risk. Conclusion: Our study provided evidence that adolescents with MDD experienced a higher prevalence of frequent nightmares and suffered more nightmare distress. Nightmare distress is an independent risk factor for suicide risk.

[The regulation of Na+/H+ exchangers by Toll-like receptors under inflammation].

Toll-like receptors (TLRs) can be recognized and activated by different pathogen associated molecular patterns (PAMPs), which induce innate immune response and inflammation of the body. Na+/H+ exchangers (NHEs) not only play roles in the regulation of cellular pH and cell volume, maintenance of the cavity microenvironment and nutrients absorption, but also are related to cell proliferation, migration and apoptosis. The activity and membrane protein expression of NHEs are inhibited under the inflammation condition. It has been shown that the activation of TLR2 in colon epithelial cells can inhibit the activity of NHE1 through MyD88 independent pathway, which involves the recruitment of Src and the phosphorylation of PI3Ks. Other studies on intestinal macrophage showed long-term LPS stimulation can induce TLR4 activation through MyD88-dependent pathway (TLR4/MyD88/NF-κB) and induce inflammation and degeneration of intracellular NHE1, which leads to NHE1 activity inhibition. But short-term LPS exposure increases the activity and protein expression of NHE1. The activation of TLR5 increases the activity of NHE3. The activity and/or expression of NHE3 in intestinal macrophages in colitis patients and model animals were decreased. In renal tubular epithelial cells, basolateral LPS stimulation inhibits luminal NHE3 activation through TLR4/MyD88-dependent MAPK/ERK signaling pathway. And LPS stimulation on the lumen side activates TLR4/MyD88-dependent PI3K-AKT-mTOR signaling pathway, which results in the inhibition of NHE1 activity in basolateral side, and then affects the NHE3 function of the lumen side.