Acupuncture combined with cognitive-behavioural therapy for insomnia (CBT-I) in patients with insomnia: study protocol for a randomised controlled trial.

INTRODUCTION: Insomnia affects physical and mental health due to the lack of continuous and complete sleep architecture. Polysomnograms (PSGs) are used to record electrical information to perform sleep architecture using deep learning. Although acupuncture combined with cognitive-behavioural therapy for insomnia (CBT-I) could not only improve sleep quality, solve anxiety, depression but also ameliorate poor sleep habits and detrimental cognition. Therefore, this study will focus on the effects of electroacupuncture combined with CBT-I on sleep architecture with deep learning. METHODS AND ANALYSIS: This randomised controlled trial will evaluate the efficacy and effectiveness of electroacupuncture combined with CBT-I in patients with insomnia. Participants will be randomised to receive either electroacupuncture combined with CBT-I or sham acupuncture combined with CBT-I and followed up for 4 weeks. The primary outcome is sleep quality, which is evaluated by the Pittsburgh Sleep Quality Index. The secondary outcome measures include a measurement of depression severity, anxiety, maladaptive cognitions associated with sleep and adverse events. Sleep architecture will be assessed using deep learning on PSGs. ETHICS AND DISSEMINATION: This trial has been approved by the institutional review boards and ethics committees of the First Affiliated Hospital of Sun Yat-sun University (2021763). The results will be disseminated through peer-reviewed journals. The results of this trial will be disseminated through peer-reviewed publications and conference abstracts or posters. TRIAL REGISTRATION NUMBER: CTR2100052502.

Rambutan genome revealed gene networks for spine formation and aril development.

Rambutan is a popular tropical fruit known for its exotic appearance, has long flexible spines on shells, extraordinary aril growth, desirable nutrition, and a favorable taste. The genome of an elite rambutan cultivar Baoyan 7 was assembled into 328 Mb in 16 pseudo-chromosomes. Comparative genomics analysis between rambutan and lychee revealed that rambutan chromosomes 8 and 12 are collinear with lychee chromosome 1, which resulted in a chromosome fission event in rambutan (n = 16) or a fusion event in lychee (n = 15) after their divergence from a common ancestor 15.7 million years ago. Root development genes played a crucial role in spine development, such as endoplasmic reticulum pathway genes, jasmonic acid response genes, vascular bundle development genes, and K+ transport genes. Aril development was regulated by D-class genes (STK and SHP1), plant hormone and phenylpropanoid biosynthesis genes, and sugar metabolism genes. The lower rate of male sterility of hermaphroditic flowers appears to be regulated by MYB24. Population genomic analyses revealed genes in selective sweeps during domestication that are related to fruit morphology and environment stress response. These findings enhance our understanding of spine and aril development and provide genomic resources for rambutan improvement.

Assessment of Myocardial Dysfunction by Three-Dimensional Echocardiography Combined With Myocardial Contrast Echocardiography in Type 2 Diabetes Mellitus.

Background: We aimed to explore the value of combining real-time three-dimensional echocardiography (RT-3DE) and myocardial contrast echocardiography (MCE) in the left ventricle (LV) evaluating myocardial dysfunction in type 2 diabetes mellitus (T2DM) patients. Patients and Methods: A total of 58 T2DM patients and 32 healthy individuals were selected for this study. T2DM patients were further divided into T2DM without microvascular complications (n = 29) and T2DM with microvascular complications (n = 29) subgroups. All participants underwent RT-3DE and MCE. The standard deviation (SD) and the maximum time difference (Dif) of the time to the minimum systolic volume (Tmsv) of the left ventricle were measured by RT-3DE. MCE was performed to obtain the perfusion measurement of each segment of the ventricular wall, including acoustic intensity (A), flow velocity (ß), and A·ß. Results: There were significant differences in all Tmsv indices except for Tmsv6-Dif among the three groups (all P < 0.05). After heart rate correction, all Tmsv indices of the T2DM with microvascular complications group were prolonged compared with the control group (all P < 0.05). The parameters of A, ß, and A·ß for overall segments showed a gradually decreasing trend in three groups, while the differences between the three groups were statistically significant (all P < 0.01). For segmental evaluation of MCE, the value of A, ß, and A·ß in all segments showed a decreasing trend and significantly differed among the three groups (all P < 0.05). Conclusions: The RT-3DE and MCE can detect subclinical myocardial dysfunction and impaired myocardial microvascular perfusion. Left ventricular dyssynchrony occurred in T2DM patients with or without microvascular complications and was related to left ventricular dysfunction. Myocardial perfusion was reduced in T2DM patients, presenting as diffuse damage, which was aggravated by microvascular complications in other organs.

Machine Learning-Based Ultrasomics Improves the Diagnostic Performance in Differentiating Focal Nodular Hyperplasia and Atypical Hepatocellular Carcinoma.

BACKGROUND: The typical enhancement patterns of hepatocellular carcinoma (HCC) on contrast-enhanced ultrasound (CEUS) are hyper-enhanced in the arterial phase and washed out during the portal venous and late phases. However, atypical variations make a differential diagnosis both challenging and crucial. We aimed to investigate whether machine learning-based ultrasonic signatures derived from CEUS images could improve the diagnostic performance in differentiating focal nodular hyperplasia (FNH) and atypical hepatocellular carcinoma (aHCC). PATIENTS AND METHODS: A total of 226 focal liver lesions, including 107 aHCC and 119 FNH lesions, examined by CEUS were reviewed retrospectively. For machine learning-based ultrasomics, 3,132 features were extracted from the images of the baseline, arterial, and portal phases. An ultrasomics signature was generated by a machine learning model. The predictive model was constructed using the support vector machine method trained with the following groups: ultrasomics features, radiologist's score, and combination of ultrasomics features and radiologist's score. The diagnostic performance was explored using the area under the receiver operating characteristic curve (AUC). RESULTS: A total of 14 ultrasomics features were chosen to build an ultrasomics model, and they presented good performance in differentiating FNH and aHCC with an AUC of 0.86 (95% confidence interval [CI]: 0.80, 0.89), a sensitivity of 76.6% (95% CI: 67.5%, 84.3%), and a specificity of 80.5% (95% CI: 70.6%, 85.9%). The model trained with a combination of ultrasomics features and the radiologist's score achieved a significantly higher AUC (0.93, 95% CI: 0.89, 0.96) than that trained with the radiologist's score (AUC: 0.84, 95% CI: 0.79, 0.89, P < 0.001). For the sub-group of HCC with normal AFP value, the model trained with a combination of ultrasomics features, and the radiologist's score remain achieved the highest AUC of 0.92 (95% CI: 0.87, 0.96) compared to that with the ultrasomics features (AUC: 0.86, 95% CI: 0.74, 0.89, P < 0.001) and radiologist's score (AUC: 0.86, 95% CI: 0.79, 0.91, P < 0.001). CONCLUSIONS: Machine learning-based ultrasomics performs as well as the staff radiologist in predicting the differential diagnosis of FNH and aHCC. Incorporating an ultrasomics signature into the radiologist's score improves the diagnostic performance in differentiating FNH and aHCC.

[Analysis on the atypical clinical accidents of acupuncture based on the individual factors in patients].

The hidden risk of acupuncture has become the factor of the high incidence of adverse reaction of acupuncture in clinical practice. The retrospective analysis and the typical cases analysis are especially important for the prevention from the hidden risk of acupuncture. In the paper, the relevant literatures were reviewed, the basic diseases were listed such as diabetes, hypertension and digestive gastric ulcer that were neglected by the physicians, and the adverse reactions induced by the therapeutic history and the body constitutions were analyzed. It was stated in the paper that because of the individual factors of patient, the risks of the atypical clinical accidents of acupuncture were extremely serious and easily neglected by the clinical acupuncture physicians. It is very necessary to remind the clinical acupuncture physicians to understand the basic diseases, basic treatment as well as the peculiarity of body constitution of the patients besides their chief complaints. Moreover, acupuncture should be applied very carefully after identifying the pulse condition and the contraindication so as to ensure the patient's safety and obtain the optimal efficacy.