Statistical inference of acupoint specificity: forward and reverse inference

Hybrid brain model accurately predict human procrastination behavior

Procrastination behavior is quite ubiquitous, and should warrant cautions to us owing to its significant influences in poor mental health, low subjective well-beings and bad academic performance. However, how to identify this behavioral problem have not yet to be fully elucidated. 1132 participants were recruited as distribution of benchmark. 81 high trait procrastinators (HP) and matched low trait procrastinators (LP) were screened. To address this issue, we have built upon the hybrid brain model by using hierarchical machine learning techniques to classify HP and LP with multi-modalities neuroimaging data (i.e., grey matter volume, fractional anisotropy, static/dynamic amplitude of low frequency fluctuation and static/dynamic degree centrality). Further, we capitalized on the multiple Canonical Correlation Analysis (mCCA) and joint Independent Component Analysis algorithm (mCCA + jICA) to clarify its fusion neural components as well. The hybrid brain model showed high accuracy to discriminate HP and LP (accuracy rate = 87.04%, sensitivity rate = 86.42%, specificity rate = 85.19%). Moreover, results of mCCA + jICA model revealed several joint-discriminative neural independent components (ICs) of this classification, showing wider co-variants of frontoparietal cortex and hippocampus networks. In addition, this study demonstrated three modal-specific discriminative ICs for classification, highlighting the temporal variants of brain local and global natures in ventromedial prefrontal cortex (vmPFC) and PHC in HP. To sum-up, this research developed a hybrid brain model to identify trait procrastination with high accuracy, and further revealed the neural hallmarks of this trait by integrating neuroimaging fusion data.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11571-021-09765-z.

Exploring Acupuncture Actions in the Body and Brain

Acupuncture's actions have been explained by biomedical research. However, the meridian system used in acupuncture needs further clarification. This review describes how acupuncture affects the body and brain. From the perspective of traditional East Asian medicine, the meridian system is closely connected with acupuncture's treatment effects. In the body, the indications of acupoints, primarily established based on the meridian system, have spatial symptom patterns. Spatial patterns of acupoint indications are distant from the stimulated sites and strongly associated with the corresponding meridian's route. Understanding how acupuncture works based on the original meridian system is important. From a neuroscience perspective, an acupuncture-induced sensation originates from the bottom-up action of simple needling in the peripheral receptor and the reciprocal interaction with top-down brain modulation. In the brain, enhanced bodily attention triggered by acupuncture stimulation can activate the salience network and deactivate the default mode network regardless of the actual stimulation. The application of data science technology to acupuncture research may provide new tools to uncover the principles of acupoint selection and enhance the clinical efficacy of acupuncture treatment in various diseases.

Special Issue: State of the Art in Research on Acupuncture Treatment

Acupuncture is a medical treatment that involves inserting a needle into the body [...].

Acupuncture as an adjunctive therapy for arrhythmia: a Delphi expert consensus survey

Background

Current evidence suggests that acupuncture is an effective adjunctive therapy that can bring potential benefits to patients with cardiac arrhythmias. However, there are relevant gaps in the optimal therapeutic strategy, which may cause uncertainties on the best practice of acupuncture treatment for arrhythmia. We aim to develop consensus-based recommendations for clinical guidance on acupuncture treatment of cardiac arrhythmias.

Methods

A multidisciplinary panel of specialists was invited to participate in a two-round semi-open clinical issue investigation. Meanwhile, relevant literature reviews were searched in 3 databases to provide evidence. Subsequently, an initial consensus voting list on acupuncture as an adjunctive therapy for cardiac arrhythmias was derived from the clinical investigation and literature review. Finally, 30 authoritative experts reached a consensus on the key issues of the voting list by a three-round modified Delphi survey. Consensus was defined when >80% agreement was achieved.

Results

Following the three-round Delphi survey, there were 32 items (91.43%) finally reaching consensus, including the following 5 domains: (I) the benefits of acupuncture for the appropriate population; (II) the general therapeutic principle; (III) the acupuncture strategy; (IV) the relevant adverse events; (V) others.

Conclusions

Consensus was achieved on some key elements. Given the lack of guidelines and the substantial heterogeneity of previous studies, these recommendations are of value in providing guidance for clinical practice of acupuncturists and in assisting patients with arrhythmia to obtain standardized acupuncture treatment. It also pointed out some problems that need to be carefully explored in future studies.

Effects of Stimulating Local and Distal Acupoints on Diabetic Gastroparesis: A New Insight in Revealing Acupuncture Therapeutics

One of the most important aspects of clinical acupuncture practice, like diabetic gastroparesis, is the selection of suitable acupoints. Furthermore, it is critical to examine the therapeutic impact differences between distal and local acupoints, as well as the prescription of their combination. In this study, diabetic gastroparesis rats were treated by needling Zhongwan (CV12) and Zusanli (ST36), and then used Single Photon Emission Computed Tomography-CT (SPECT-CT) technology to assess the effects of promoting gastric motility. In addition, morphological observation, immunohistochemical examination, and biomarker assays, such as determination of growth factor 1, motilin, and ghrelin contents in serum samples, were performed to better understand the impact of certain various acupuncture treatments. All of the therapies improved the symptoms of diabetic gastroparesis rats, according to the findings. Stimulating these acupoints, on the other hand, can have a different therapeutic effect. In addition, needling local and distal acupoints together can have an antagonistic or synergistic impact on specific physiological and biochemical indexes such as gastric motility, ghrelin, gastrin, and growth factor 1, among others. Our findings demonstrated the benefits of acupoints and acupuncture in the management of diabetic gastroparesis, as well as a new insight into acupuncture therapeutics.

Identification of Acupoint Indication from Reverse Inference: Data Mining of Randomized Controlled Clinical Trials

The specificity of acupoint indication (i.e., reverse inference—diseases for which an acupoint could be used) might differ from the specificity of acupoint selection (i.e., forward inference—acupoints used for a disease). In this study, we explore acupoint specificity through reverse inferences from the dataset of prescribed acupoints for a certain disease in clinical trials. We searched acupuncture treatment regimens in randomized controlled trials included in the Cochrane Database of Systematic Reviews. For forward inference, the acupoints prescribed for each disease were quantified. For reverse inference, diseases for each acupoint were quantified. Data were normalized using Z-scores. Bayes factor correction was performed to adjust for the prior probability of diseases. The specificities of acupoint selections in 30 diseases were determined using forward inference. The specificities of acupoint indications regarding 49 acupoints were identified using reverse inference and then subjected to Bayes factor correction. Two types of acupoint indications were identified for 24 acupoints: regional and distal. Our approach suggests that the specificity of acupoint indication can be inferred from clinical data using reverse inference. Acupoint indication will improve our understanding of acupoint specificity and will lead to the establishment of a new model of analysis and educational resources for acupoint characteristics.

A Key Node Mining Method Based on Acupoint-Disease Network (ADN): A New Perspective for Exploring Acupoint Specificity

In the process of treating pro-diseases with acupuncture, traditional Chinese medicine (TCM) doctors may fine-tune acupuncture prescriptions according to different prior experiences. Different prescriptions will affect the efficiency and effect of acupuncture treatment, and even excessive acupoint selection may cause psychological pressure on patients. We still lack an effective means to analyze the meridian system and acupoint specificity to clarify the mapping relationship between acupoints and diseases. Given the inability of modern medical technology to provide effective evidence support for meridians and acupoints, we combined acupuncture theory with network science for an interdisciplinary discussion. In this paper, we constructed a weighted undirected acupoint-disease network (ADN) based on clinical acupuncture prescription literature and proposed a high-specificity key node mining method based on ADN. Combined with the principle of acupoint selection in TCM, the proposed method balanced the contribution of local areas to the network based on the distribution characteristics of meridians and selected 30 key acupoints with high influence on the global topology according to the evaluation index of key nodes. Finally, we compared the proposed method with the other six classical node importance evaluation algorithms in terms of resolution, network loss, and accuracy. The comprehensive results show that the marked key acupoint nodes make outstanding contributions to the connectivity, topological structure, and weighted benefits of the network, and the stability and specificity of the algorithm guarantee the reliability of the key acupoint nodes. We consider that these key acupoints with high centrality in ADN can be used as core acupoints to help researchers explore targeted and high-impact acupoint combinations under resource constraints and optimize existing acupuncture prescriptions.