Acupressure: a possible therapeutic strategy for anxiety related to COVID-19: a meta-analysis of randomized controlled trials.

Background: From the end of 2019 to December 2023, the world grappled with the COVID-19 pandemic. The scope and ultimate repercussions of the pandemic on global health and well-being remained uncertain, ushering in a wave of fear, anxiety, and worry. This resulted in many individuals succumbing to fear and despair. Acupoint massage emerged as a safe and effective alternative therapy for anxiety relief. However, its efficacy was yet to be extensively backed by evidence-based medicine. This study aimed to enhance the clinical effectiveness of acupoint massage and extend its benefits to a wider population. It undertakes a systematic review of the existing randomized controlled trials (RCTs) assessing the impact of acupoint massage on anxiety treatment, discussing its potential benefits and implications. This research aims to furnish robust evidence supporting anxiety treatment strategies for patients afflicted with COVID-19 disease and spark new approaches to anxiety management. Objectives: This study evaluates the evidence derived from randomised controlled trials (RCTs), quantifies the impact of acupressure on anxiety manifestations within the general population, and proposes viable supplementary intervention strategies for managing COVID-19 related anxiety. Materials and methods: This review included RCTs published between February 2014 and July 2023, that compared the effects of acupressure with sham control in alleviating anxiety symptomatology as the outcome measure. The studies were sourced from the multiple databases, including CINAHL, EBM Reviews, Embase, Medline, PsycINFO, Scopus and Web of Science. A meta-analysis was performed on the eligible studies, and an overall effect size was computed specifically for the anxiety outcome. The Cochrane Collaboration Bias Risk Assessment Tool (RevMan V5.4) was employed to assess bias risk, data integration, meta-analysis, and subgroup analysis. The mean difference, standard mean deviation, and binary data were used to represent continuous outcomes. Results: Of 1,110 studies of potential relevance, 39 met the criteria for inclusion in the meta-analysis. The majority of the studies reported a positive effect of acupressure in assuaging anticipatory anxiety about treatment. Eighteen studies were evaluated using the STAI scale. The acupressure procedures were thoroughly documented, and studies exhibited a low risk of bias. The cumulative results of the 18 trials showcased a more substantial reduction in anxiety in the acupressure group compared to controls (SMD = -5.39, 95% CI -5.61 to -5.17, p < 0.01). A subsequent subgroup analysis, based on different interventions in the control group, demonstrated improvement in anxiety levels with sham acupressure in improving changes in anxiety levels (SMD -1.61, 95% CI: -2.34 to -0.87, p < 0.0001), and blank controls (SMD -0.92, 95% CI: -2.37 to 0.53, p = 0.22). Conclusion: In the clinical research of traditional Chinese medicine treatment of anxiety, acupressure demonstrated effectiveness in providing instant relief from anxiety related to multiple diseases with a medium effect size. Considering the increasing incidence of anxiety caused by long COVID, the widespread application of acupressure appears feasible. However, the results were inconsistent regarding improvements on physiological indicators, calling for more stringent reporting procedures, including allocation concealment, to solidify the findings.

Cloning and Expression Analysis of Key Enzyme Gene CoGPPS Involved in Iridoid Glycoside Synthesis in Cornus officinalis.

Cornus iridoid glycosides (CIGs), including loganin and morroniside, are the main active components of Cornus officinalis. As one of the key enzymes in the biosynthesis of CIGs, geranyl pyrophosphate synthase (GPPS) catalyzes the formation of geranyl pyrophosphate, which is the direct precursor of CIGs. In this study, the C. officinalis geranyl pyrophosphate synthase (CoGPPS) sequence was cloned from C. officinalis and analyzed. The cDNA sequence of the CoGPPS gene was 915 bp (GenBank No. OR725699). Phylogenetic analysis showed that CoGPPS was closely related to the GPPS sequence of Actinidia chinensis and Camellia sinensis, but relatively distantly related to Paeonia lactiflora and Tripterygium wilfordii. Results from the quantitative real-time PCR showed the spatiotemporal expression pattern of CoGPPS; that is, CoGPPS was specifically expressed in the fruits. Subcellular localization assay proved that CoGPPS was specifically found in chloroplasts. Loganin and morroniside contents in the tissues were detected by high-performance liquid chromatography, and both compounds were found to be at higher levels in the fruits than in leaves. Thus, this study laid the foundation for further studies on the synthetic pathway of CIGs.

Radiomics signatures for predicting the Ki-67 level and HER-2 status based on bone metastasis from primary breast cancer.

This study explores the potential of radiomics to predict the proliferation marker protein Ki-67 levels and human epidermal growth factor receptor 2 (HER-2) status based on MRI images of patients with spinal metastasis from primary breast cancer. A total of 110 patients with pathologically confirmed spinal metastases from primary breast cancer were enrolled between Dec. 2017 and Dec. 2021. All patients underwent T1-weighted contrast-enhanced MRI scans. The PyRadiomics package was used to extract features from the MRI images based on the intraclass correlation coefficient and least absolute shrinkage and selection operator. The most predictive features were used to develop the radiomics signature. The Chi-Square test, Fisher's exact test, Student's t-test, and Mann-Whitney U test were used to evaluate the clinical and pathological characteristics between the high- and low-level Ki-67 groups and the HER-2 positive/negative groups. The radiomics models were compared using receiver operating characteristic curve analysis. The area under the receiver operating characteristic curve (AUC), sensitivity (SEN), and specificity (SPE) were generated as comparison metrics. From the spinal MRI scans, five and two features were identified as the most predictive for the Ki-67 level and HER-2 status, respectively. The developed radiomics signatures generated good prediction performance for the Ki-67 level in the training (AUC = 0.812, 95% CI: 0.710-0.914, SEN = 0.667, SPE = 0.846) and validation (AUC = 0.799, 95% CI: 0.652-0.947, SEN = 0.722, SPE = 0.833) cohorts. Good prediction performance for the HER-2 status was also achieved in the training (AUC = 0.796, 95% CI: 0.686-0.906, SEN = 0.720, SPE = 0.776) and validation (AUC = 0.705, 95% CI: 0.506-0.904, SEN = 0.733, SPE = 0.762) cohorts. The results of this study provide a better understanding of the potential clinical implications of spinal MRI-based radiomics on the prediction of Ki-67 levels and HER-2 status in breast cancer.