The effective on intradermal acupuncture based on changes in biological specificity of acupoints for major depressive disorder: study protocol of a prospective, multicenter, randomized, controlled trial

BackgroundAntidepressants still have some side effects in treating major depressive disorder (MDD), and acupuncture therapy is a complementary therapy of research interest for MDD. Acupoints are sensitive sites for disease response and stimulation points for acupuncture treatment. Prior studies suggest that the biological specificity of acupoints is altered in physiological and pathological situations. Therefore, we hypothesize that the biological specificity of acupoints is associated with the diagnosis of MDD and that stimulating acupoints with significant biological specificity can achieve a better therapeutic effect than clinical common acupoints. This study aims to investigate the efficacy and safety of intradermal acupuncture (IA) treatment for MDD based on changes in the biological specificity of acupoints.MethodsThe first part of the study will enroll 30 MDD patients and 30 healthy control (HC) participants to assess pain sensitivity and thermal specificity of MDD-related acupoints using a pressure pain threshold gauge (PTG) and infrared thermography (IRT). The potentially superior acupoints for treating MDD will be selected based on the results of PTG and IRT tests and referred to as pressure pain threshold strong response acupoints (PSA) and temperature strong response acupoints (TSA).The second part of the study will enroll 120 eligible MDD patients randomly assigned to waiting list (WL) group, clinical common acupoint (CCA) group, TSA group, and PSA group in a 1:1:1:1 ratio. The change in the Patient Health Questionnaire-9 Items (PHQ-9), the MOS item short-form health survey (SF-36), pressure pain threshold, temperature of acupoints, and adverse effects will be observed. The outcomes of PHQ-9 and SF-36 measures will be assessed before intervention, at 3 and 6 weeks after intervention, and at a 4-week follow-up. The biological specificity of acupoint measures will be assessed before intervention and at 6 weeks after intervention. All adverse effects will be assessed.DiscussionThis study will evaluate the therapeutic effect and safety of IA for MDD based on changes in the biological specificity of acupoints. It will investigate whether there is a correlation between the biological specificity of MDD-related acupoints and the diagnosis of MDD and whether stimulating strong response acupoints is superior to clinical common acupoints in the treatment of MDD. The study’s results may provide insights into the biological mechanisms of acupuncture and its potential as a complementary therapy for MDD.Clinical Trial RegistrationClinicalTrials.gov, identifier: NCT05524519

Transparent Shape from a Single View Polarization Image

This paper presents a learning-based method for transparent surface estimation from a single view polarization image. Existing shape from polarization(SfP) methods have the difficulty in estimating transparent shape since the inherent transmission interference heavily reduces the reliability of physics-based prior. To address this challenge, we propose the concept of physics-based prior, which is inspired by the characteristic that the transmission component in the polarization image has more noise than reflection. The confidence is used to determine the contribution of the interfered physics-based prior. Then, we build a network(TransSfP) with multi-branch architecture to avoid the destruction of relationships between different hierarchical inputs. To train and test our method, we construct a dataset for transparent shape from polarization with paired polarization images and ground-truth normal maps. Extensive experiments and comparisons demonstrate the superior accuracy of our method. Our codes and data are provided in the supplements

Location and Pictures of Reshui-1 tomb relative to the locations of the dated tombs (No. XTT, ZGR, DRX and DRN3) in Dulan and Delingha areas.

<p>XTT includes four tombs [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0133438#pone.0133438.ref026" target="_blank">26</a>] and DRX includes 7 tombs (00DRXM3, 00DRXM8, 00DRXM10, 00DRXM14, 00DRXM19, 00DRXM21, 00DRXM23) [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0133438#pone.0133438.ref026" target="_blank">26</a>]. Picture a) Signage of the Reshui Tomb Cluster; b) Full view of the Reshui-1 Tomb (from west); c) Collapsed portion of the tomb roof and the exposed roofing beams.</p

Surrogate Model via Artificial Intelligence Method for Accelerating Screening Materials and Performance Prediction

International audiencePredicting the performance of mechanical properties is an important and current issue in the field of engineering and materials science, but traditional experiments and modeling calculations often consume large amounts of time and resources. Therefore, it is imperative to use appropriate methods to accelerate the process of material selection and design. The artificial intelligence method, particularly deep learning models, has been verified as an effective and efficient method for handling computer vision and neural language problems. In this paper, a deep learning surrogate model (DLS) is proposed for predicting the mechanical performance of materials, that is, the maximum stress value under complex working conditions. The DLS can reproduce the finite element analysis model results with 98.79% accuracy. The results show that deep learning has great potential. This research also provides a new approach for material screening in practical engineering

Results from the COFECHA correlation analysis conducted for tree-ring measurements of the sixteen sample series from the Reshui-1 Tomb.

<p>Results from the COFECHA correlation analysis conducted for tree-ring measurements of the sixteen sample series from the Reshui-1 Tomb.</p

Correlation coefficients between the 16 dated sample series and the three reference chronologies (QC, ZDC, and SDC).

<p>Correlation coefficients between the 16 dated sample series and the three reference chronologies (QC, ZDC, and SDC).</p

COFECHA output showing the top six best dating adjustments (“Add”) based on the six highest correlation coefficients (“Corr #”) for RS01, 03, 13 against QAC in 50-year long segments (25-year lags).

<p>The years underlined are the final choices.</p

Correlation coefficients between the first 50-year segment of sample RS01 and QAC as the moving window shifted from -10 to +10 years of a potential target date with a one-year lag.

<p>Please refer to the text for details.</p

Seven Qilian juniper discs sampled from the fallen roofing beams of the Reshui-1 Tomb.

<p>Seven Qilian juniper discs sampled from the fallen roofing beams of the Reshui-1 Tomb.</p