Mechanisms of action of Shizhenqing granules for eczema treatment: Network pharmacology analysis and experimental validation.

Background: Jiuwan decoction has been used to treat chronic eczema since the Qing Dynasty. According to clinical experience, Shizhenqing granules (SZQG), derived from the Jiuwan decoction, exert beneficial clinical effects on acute eczema and reduce recurrence. Therefore, we elucidated the underlying mechanisms of SZQG through network pharmacology, molecular docking, and experimental validation. Methods: The main chemical components of SZQG were identified by ultra-high-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS). And the targets of SZQG against eczema were screened out through online databases. Then, the regulatory network map of the "herbal compound-potential target" and the target protein-protein interaction (PPI) network was constructed. The Gene Ontology (GO) analysis and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were conducted using by R language. Additionally, the interaction between the active compounds and the targets was verified by molecular docking technology. Finally, an experiment in vivo was used to verify the effect and mechanism of SZQG on eczema. Results: Using UHPLC-MS/MS, 158 main chemical compounds of SZQG were identified, and 72 compounds were selected according to the criteria for further analysis. All 237 potential targets of SZQG in eczema were explored using multiple online databases. The network with 14 core targets was screened out, including STAT3, RELA, TNF, JUN, MAPK3, IL-6, PIK3CA, STAT1, MAPK14, MAPK1, IL-4, NFKBIA, IL1B, and MYC. KEGG analyses indicated that the therapeutic effects of SZQG on eczema were predominantly associated with cytokine-cytokine receptor interaction, TNF, MAPK, NF-κB, toll-like receptor, T cell receptor, and Th1 and Th2 cell differentiation signaling pathways. Furthermore, the good affinity between the core compounds and core targets was verified by molecular docking technology, particularly for RELA and MAPK. Animal experiments revealed that SZQG downregulated MAPK14, RELA, T-bet, and GATA3 mRNA expression, reduced immunoglobulin E (IgE) and interleukin-4 (IL-4) serum concentrations, and improved eczema-like lesions in model rats. Conclusion: This study identified potential targets and signaling pathways of SZQG in the treatment of eczema, whereby RELA and MAPK14 may constitute the main therapeutic targets of SZQG in cytokine regulation and reduction of inflammatory responses.

Graph embedding-based heterogeneous domain adaptation with domain-invariant feature learning and distributional order preserving.

Heterogeneous domain adaptation (HDA) methods leverage prior knowledge from the source domain to train models for the target domain and address the differences in their feature spaces. However, incorrect alignment of categories and distribution structure disruption may be caused by unlabeled target samples during the domain alignment process for most existing methods, resulting in negative transfer. Additionally, the previous works rarely focus on the robustness and interpretability of the model. To address these issues, we propose a novel Graph embedding-based Heterogeneous domain-Invariant feature learning and Distributional order preserving framework (GHID). Specifically, a bidirectional robust cross-domain alignment graph embedding structure is proposed to globally align two domains, which learns the domain-invariant and discriminative features simultaneously. In addition, the interpretability of the proposed graph structures is demonstrated through two theoretical analyses, which can elucidate the correlation between important samples from a global perspective in heterogeneous domain alignment scenarios. Then, a heterogeneous discriminative distributional order preserving graph embedding structure is designed to preserve the original distribution relationship of each domain to prevent negative transfer. Moreover, the dynamic centroid strategy is incorporated into the graph structures to improve the robustness of the model. Comprehensive experimental results on four benchmarks demonstrate that the proposed method outperforms other state-of-the-art approaches in effectiveness.

Precision Therapy of Recurrent Breast Cancer through Targeting Different Malignant Tumor Cells with a HER2/CD44-Targeted Hydrogel Nanobot.

Heterogeneity and drug resistance of tumor cells are the leading causes of incurability and poor survival for patients with recurrent breast cancer. In order to accurately deliver the biological anticancer drugs to different subtypes of malignant tumor cells for omnidirectional targeted treatment of recurrent breast cancer, a distinct design is demonstrated by embedding liposome-based nanocomplexes containing pro-apoptotic peptide and survivin siRNA drugs (LPR) into Herceptin/hyaluronic acid cross-linked nanohydrogels (Herceptin-HA) to fabricate a HER2/CD44-targeted hydrogel nanobot (named as ALPR). ALPR delivered cargoes to the cells overexpressing CD44 and HER2, followed by Herceptin-HA biodegradation, subsequently, the exposed lipid component containing DOPE fused with the endosomal membrane and released peptide and siRNA into the cytoplasm. These experiments indicated that ALPR can specifically deliver Herceptin, peptide, and siRNA drugs to HER2-positive SKBR-3, triple-negative MDA-MB-231, and HER2-negative drug-resistant MCF-7 human breast cancer cells. ALPR completely inhibited the growth of heterogeneous breast tumors via multichannel synergistic effects: disrupting mitochondria, downregulating the survivin gene, and blocking HER2 receptors on the surface of HER2-positive cells. The present design overcomes the chemical drug resistance and opens a feasible route for the combinative treatment of recurrent breast cancer, even other solid tumors, utilizing different kinds of biological drugs.

Ultrafast Charge Carrier Dynamics in InP/ZnSe/ZnS Core/Shell/Shell Quantum Dots.

The excellent performance of InP/ZnSe/ZnS core/shell/shell quantum dots (CSS-QDs) in light-emitting diodes benefits from the introduction of a ZnSe midshell. Understanding the changes of ultrafast carrier dynamics caused by the ZnSe midshell is important for their optoelectronic applications. Herein, we have compared the ultrafast carrier dynamics in CSS-QDs and InP/ZnS core/shell QDs (CS-QDs) using femtosecond transient absorption spectroscopy. The results show that the ZnSe midshell intensifies the electron delocalization and prolongs the in-band relaxation time of electrons from 238 fs to 350 fs, and that of holes from hundreds of femtoseconds to 1.6 ps. We also found that the trapping time caused by deep defects increased from 25.6 ps to 76 ps, and there were significantly reduced defect emissions in CSS-QDs. Moreover, the ZnSe midshell leads to a significantly increased density of higher-energy hole states above the valence band-edge, which may reduce the probability of Auger recombination caused by the positive trion. This work enhances our understanding of the excellent performance of the CSS-QDs applied to light-emitting diodes, and is likely to be helpful for the further optimization and design of optoelectronic devices based on the CSS-QDs.

Fuzzy Discriminative Block Representation Learning for Image Feature Extraction.

Representation learning is widely used to project high-dimensional data to low-dimensional subspace for feature extraction in image recognition tasks. However, many related methods barely explore the fuzziness and uncertainty between data classes. Besides, the classical unsupervised sparse constraint weakens the evaluation of feature importance and neglects the preservation of discriminant information during sparse representation. To solve these issues, a novel fuzzy discriminative block representation learning (FDBRL) algorithm is proposed for image feature extraction. FDBRL aims to enhance the discriminability of subspace by designing effective constraints for projection learning. Specifically, based on the label information and the fuzzy relation between data, we construct a fuzzy block weight matrix and embed it into the l2,1 norm regularization term to realize supervised sparse constraint for the representation learning. Next, the low-rank constraint is used to capture the inherent global structure information of data. Finally, we introduce a classification loss term with transformation matrix for joint optimization, such that the projection learning is not limited to number of classes, and the discriminative ability is further improved. Comprehensive experimental results on six benchmarks verify that our method achieves promising performance with other state-of-the-arts in both robustness and effectiveness.

A Spatiotemporal Convolutional Network for Multi-Behavior Recognition of Pigs.

The statistical data of different kinds of behaviors of pigs can reflect their health status. However, the traditional behavior statistics of pigs were obtained and then recorded from the videos through human eyes. In order to reduce labor and time consumption, this paper proposed a pig behavior recognition network with a spatiotemporal convolutional network based on the SlowFast network architecture for behavior classification of five categories. Firstly, a pig behavior recognition video dataset (PBVD-5) was built by cutting short clips from 3-month non-stop shooting videos, which was composed of five categories of pig's behavior: feeding, lying, motoring, scratching and mounting. Subsequently, a SlowFast network based spatiotemporal convolutional network for the pig's multi-behavior recognition (PMB-SCN) was proposed. The results of the networks with variant architectures of the PMB-SCN were implemented and the optimal architecture was compared with the state-of-the-art single stream 3D convolutional network in our dataset. Our 3D pig behavior recognition network showed a top-1 accuracy of 97.63% and a views accuracy of 96.35% on the test set of PBVD and a top-1 accuracy of 91.87% and a views accuracy of 84.47% on a new test set collected from a completely different pigsty. The experimental results showed that this network provided remarkable ability of generalization and possibility for the subsequent pig detection and behavior recognition simultaneously.

Studies on fault diagnosis of dissolved oxygen sensor based on GA-SVM.

The present research envisaged the analysis of the dissolved oxygen fault of the water quality monitoring system using the genetic algorithm-support vector machine (GA-SVM). The real-time data collected by the dissolved oxygen sensor was classified into the fault types. The fault types were divided into complete failure fault, impact fault, and constant output fault. Based on the fault classification of the dissolved oxygen parameters, SVM fault diagnosis experiments were conducted. Experimental results show that the accuracy of dissolved oxygen was 98.53%. On comparison with the experimental results of the back propagation (BP) neural network, it was found that the diagnosis results of the dissolved oxygen parameters using SVM were better than those of the BP neural network. The genetic algorithm (GA) was used to optimize the parameters. After iteration, the optimal parameters such as C and g were selected (C is the penalty coefficient, which adjusts the weight of the two index preferences in the optimization direction, i.e., the tolerance for errors, and g is a parameter that comes with the function that implicitly determines the distribution of the data after mapping to the new feature space.). By using GA, after iteration, the optimized values of C and g was found to be 2.1649 and 5.3312, respectively. The experimental results showed that the method exhibited a good accuracy.

The mediating role of perceived prejudice in the relationship between self-esteem and psychological distress among Chinese male nursing students.

Male nursing students may experience social prejudice, which may lead to psychological distress. However, few quantitative studies have focused on their mental health. This study aimed to explore the relationship among self-esteem, perceived prejudice, and psychological distress in male nursing students, and compare differences in self-esteem, perceived prejudice, and psychological distress, as well as the relationships among these variables between male nursing students who selected nursing as their first choice for a major and those who did not. A survey based on a cross-sectional design was used. Self-esteem, perceived prejudice, and psychological distress of 460 male nursing students in China were measured using the Rosenberg Self-esteem Scale, a self-developed questionnaire, and the Kessler 10, respectively. Structural equation modeling was adopted to test the theoretical model regarding the relationships among self-esteem, perceived prejudice, and psychological distress. The results indicated that 82.2% of the participants reported psychological distress. The participants who did not select nursing as their first choice for a major reported a significantly higher perceived prejudice, higher prevalence of psychological distress, and lower self-esteem. Therefore, when selecting male students, nursing schools must prioritize those who selected nursing as their first choice for a major.

Mounting Behaviour Recognition for Pigs Based on Deep Learning.

For both pigs in commercial farms and biological experimental pigs at breeding bases, mounting behaviour is likely to cause damage such as epidermal wounds, lameness and fractures, and will no doubt reduce animal welfare. The purpose of this paper is to develop an efficient learning algorithm that is able to detect the mounting behaviour of pigs based on the data characteristics of visible light images. Four Göttingen minipigs were selected as experimental subjects and were monitored for a week by a camera that overlooked the pen. The acquired videos were analysed and the frames containing mounting behaviour were intercepted as positive samples of the dataset, and the images with inter-pig adhesion and separated pigs were taken as negative samples. Pig segmentation network based on Mask Region-Convolutional Neural Networks (Mask R-CNN) was applied to extract individual pigs in the frames. The region of interest (RoI) parameters and mask coordinates of each pig, from which eigenvectors were extracted, could be obtained. Subsequently, the eigenvectors were classified with a kernel extreme learning machine (KELM) to determine whether mounting behaviour has occurred. The pig segmentation presented considerable accuracy and mean pixel accuracy (MPA) with 94.92% and 0.8383 respectively. The presented method showed high accuracy, sensitivity, specificity and Matthews correlation coefficient with 91.47%, 95.2%, 88.34% and 0.8324 respectively. This method can be an efficient way of solving the problem of segmentation difficulty caused by partial occlusion and adhesion of pig bodies, even if the pig body colour was similar to the background, in recognition of mounting behaviour.

Low post-traumatic stress disorder rate in Chinese in Beijing, China.

OBJECT: There have been significantly fewer community-based, epidemiological studies focusing on PTSD and its socio-demographic correlates among the Chinese than Western populations. METHOD: The multistage household cluster random sampling method was used to select participants from18 districts and counties in Beijing; a total of 16,032 participants were assessed; face-to-face interviews and data collection was conducted using the semi-structured clinical interview for DSM-IV-TR Axis I Disorders-Patient Edition (SCID-I/P). RESULT: The lifetime PTSD prevalence was 0.3%. Older age, low educational level, low personal monthly income, urban living, unemployment and being a farmer were all significantly associated with an increased risk of PTSD. Multivariate analysis showed that farmers and the unemployed were significantly associated with a higher risk for PTSD. CONCLUSIONS: The prevalence rates of PTSD in Beijing were low compared with that of Western countries. Farming occupation and unemployment were independent risk factors for PTSD.

Effect of inserted spacer in hepatic cell-penetrating multifunctional peptide component on the DNA intracellular delivery of quaternary complexes based on modular design.

A safe and efficient quaternary gene delivery system (named Q-complexes) was constructed based on self-assembly of molecules through noncovalent bonds. This system was formulated through the cooperation and competing interactions of cationic liposomes, multifunctional peptides, and DNA, followed by coating hyaluronic acid on the surface of the ternary complexes. The multifunctional peptide was composed of two functional domains: penetrating hepatic tumor-targeted cell moiety (KRPTMRFRYTWNPMK) and a wrapping gene sequence (polyarginine 16). The effect of spacer insertion between the two domains of multifunctional peptide on the intracellular transfection of Q-complexes was further studied. Experimental results showed that the formulations assembled with various peptides in the spacer elements possessed different intercellular pathways and transfection efficiencies. The Q-complexes containing peptide in the absence of spacer element (Pa) showed the highest gene expression among all samples. The Q-complexes containing peptides with a noncleavable spacer GA (Pc) had no ability of intracellular nucleic acid delivery, whereas those with a cleavable spacer RVRR (Pd) showed moderate transfection activity. These results demonstrated that the different spacers inserted in the multifunctional peptide played an important role in in vitro DNA transfection efficiency. Atomic force microscopy images showed that the morphologies of ternary complexes (LPcD) and Q-complexes (HLcPD) were crystal lamellas, whereas those of other nanocomplexes were spheres. Circular dichroism showed the changed configuration of peptide with spacer GA in nanocomplexes compared with that of its free state, whereas the Pa configuration without spacer in nanocomplexes was consistent with that of its free state. The present study contributed to the structural understanding of Q-complexes, and further effective modification is in progress.

Prevalence of major depressive disorder and socio-demographic correlates: Results of a representative household epidemiological survey in Beijing, China.

BACKGROUND: Major depressive disorder (MDD) is the most prevalent mental disorder in the general population and has been associated with socioeconomic factors. Beijing has undergone significant socioeconomic changes in last decade, however no large-scale community epidemiological surveys of MDD have been conducted in Beijing since 2003. AIMS: To determine the prevalence of MDD and its socio-demographic correlates in a representative household sample of the general population in Beijing, China. METHOD: Data were collected from the 2010 representative household epidemiological survey of mental disorders in Beijing. The multistage cluster random sampling method was used to select qualified subjects in 18 districts and counties, and then face-to-face interviews were administered using the Chinese version of Structured Clinical Interview for DSM-IV-TR Axis I Disorders-Patient Edition (SCID-I/P) during November 1, 2010 to December 31, 2010. RESULTS: 19,874 registered permanent residents were randomly identified and 16,032 (response rate=80.7%) completed face-to-face interviews. The time-point and life-time prevalence rates of MDD were estimated to be 1.10% (95% CI: 0.94-1.26%) and 3.56% (95% CI: 3.27-3.85%) respectively. Significant differences were found in sex, age, location of residence, marital status, education, employment status, personal/family monthly income, perception of family environment and relationship with others, when comparing residents with MDD to those without MDD. Those who were female, aged 45 or above, reported low family income, or reported an "average" or "poor" family environment were associated with a higher risk of MDD. CONCLUSIONS: The prevalence of MDD reported in this survey is relatively lower than that in other western countries. Female sex, age older than 45, low family income, and poor family environment appear to be independent risk factors for MDD.

Superoxide scavenging and Akt inhibition in myocardium ameliorate pressure overload-induced NF-κB activation and cardiac hypertrophy.

Recent studies from our laboratory and others have shown that increases in cytoplasmic superoxide (O(2)(·-)) levels and Akt activation play a key role in agonist-stimulated NF-κB activation and cardiomyocyte hypertrophy in vitro. In this study, we tested the hypothesis that adenovirus (Ad)-mediated intramyocardial gene transfer of cytoplasmic superoxide dismutase (AdCu/ZnSOD) or a dominant-negative form of Akt (AdDNAkt) in mice would attenuate pressure overload-induced increases in activation of the redox-sensitive transcription factor NF-κB and cardiac hypertrophy. Adult C57BL/6 mice were subjected to thoracic aortic banding (TAB) or sham surgery, and intramyocardial injections of viral vectors (AdCu/ZnSOD, AdDNAkt, or control) were performed. There was robust transgene expression in the heart, which peaked 6-7 days after injection and then declined to undetectable levels by 12-14 days. In mice injected with AdBgL II, TAB caused a significant increase in O(2)(·-) generation and cardiac mass at 1 wk, and these responses were markedly attenuated by AdCu/ZnSOD. In addition, TAB induced time-dependent activation of NF-κB in the myocardium as measured longitudinally by in vivo bioluminescent imaging of NF-κB-dependent luciferase expression. This was also abolished by intracardiac AdCu/ZnSOD or AdDNAkt, but not the control vector. The inhibition of Akt and O(2)(·-)-mediated NF-κB activation in TAB hearts was associated with an attenuation of cardiac hypertrophy. Since a direct cause-and-effect relationship between NF-κB activation and cardiomyocyte hypertrophy has been established previously, our data support the hypothesis that increased O(2)(·-) generation and Akt activation are key signaling intermediates in pressure overload-induced activation of NF-κB and cardiac hypertrophy.

Relationships of sleep duration with sleep disturbances, basic socio-demographic factors, and BMI in Chinese people.

OBJECTIVE: This study aimed at determining the mean total sleep time (TST) and the relationship between sleep duration and basic socio-demographic factors and BMI sleep problems in Chinese subjects. METHOD: A total of 5926 subjects were randomly selected and interviewed using standardized assessment tools. RESULTS: The reported mean TST was 7.76 h. Short sleepers were significantly older than medium and long sleepers. There were more urban residents who were short sleepers than medium and long sleepers. Short sleepers reported more sleep problems than medium and long sleepers. Short and long sleepers reported more psychiatric disorders than medium sleepers in both sexes, and short sleepers also had more major medical conditions in women. Short sleepers had a lower BMI than medium and long sleepers after controlling for the effects of age and psychiatric disorders in women. CONCLUSIONS: Nationwide epidemiologic surveys in China are needed to further explore the relationship between sleep duration and sleep problems.

Alcohol-related disorders in Beijing, China: prevalence, socio-demographic correlates, and unmet need for treatment.

BACKGROUND: The study aimed to determine the prevalence of alcohol use, episodic heavy drinking, and alcohol dependence and their socio-demographic correlates in Beijing, China. methods: A total of 5,926 subjects were randomly selected in Beijing and interviewed using the Composite International Diagnostic Interview (CIDI 1.0). Data on basic socio-demographic and current major medical conditions were also collected. RESULTS: The 12-month prevalence of alcohol use and episodic heavy drinking were 32.5 and 13.8%, respectively. The 12-month and lifetime prevalence of alcohol dependence were 1.7 and 4.3%, respectively. Age above 24 years, male sex, being married and employed, low education level (junior high school, primary school or illiterate), rural residence, and having comorbid psychiatric disorders were all significantly associated with a higher likelihood of alcohol-related disorders. Only 2.4% of the subjects with alcohol dependence were receiving treatment, and a mere 1.4% had sought treatment from mental health professionals. CONCLUSIONS: Nationwide surveys are urgently needed to further explore the prevalence of alcohol-related disorders in China.

Generalized anxiety disorder in China: prevalence, sociodemographic correlates, comorbidity, and suicide attempts.

PURPOSE: This study aims to determine the 12-month and lifetime prevalence of generalized anxiety disorder (GAD) and its sociodemographic correlates. DESIGN AND METHODS: A total of 5,926 subjects were randomly selected and interviewed. FINDINGS: The overall 12-month and lifetime prevalence of GAD was 0.8%, and 1.2%, respectively. Being older than 25 years and female, lower education level, unemployed status, and lower (RMB2000/month) monthly income were associated with increased risk of GAD. PRACTICE IMPLICATIONS: The low percentage of subjects treated for GAD indicates a major public health problem that should be addressed.

Lifetime prevalence of suicidal ideation, suicide plans and attempts in rural and urban regions of Beijing, China.

OBJECTIVE: There has been no large-scale survey of suicide-related behaviours including suicidal ideations, plans and attempts in China involving both rural and urban areas and using standardized assessment tools. The aim of the present study was to determine the lifetime prevalence of suicide-related behaviour and its relationship with sociodemographic factors and psychiatric disorders in the rural and urban regions of Beijing, China. METHODS: A total of 5926 subjects were randomly selected in Beijing and interviewed using the Composite International Diagnostic Interview. Basic sociodemographic and clinical data and data on suicide-related behaviour were also collected. RESULTS: The overall lifetime prevalence estimates of suicidal ideation, plans and attempts were 2.3%, 1.4%, and 1.0%, respectively; the corresponding figures were 2.8%, 1.6%, and 1.3% in the rural sample, and 1.8%, 1.3%, and 0.9% in the urban sample. Age (>25 years), female sex, unmarried status, lower education level, lower (RMB2000 month(-1)) monthly income and presence of major medical disorders were significantly associated with increased risk of suicide-related behaviour. 36.2% of subjects with suicide-related behavior consulted a medical practitioner and 20.7% consulted a psychiatrist. CONCLUSIONS: The prevalence of lifetime suicide-related behaviour in Beijing is lower than in Western countries, but the low percentage of subjects treated for suicide-related behaviour indicates a major public health problem that should be addressed. National surveys are needed to further explore the prevalence of suicide-related behaviour in China.

Smoking and psychiatric disorders in the rural and urban regions of Beijing, China: a community-based survey.

BACKGROUND: In China, there is limited information on smoking and its socio-demographic correlates in general, and in psychiatric patients in particular. The aim of this study was to determine the prevalence of lifetime, current mild, and heavy smoking, the socio-demographic correlates of current smoking, and its relationship with psychiatric disorders in the Beijing municipality, China. METHODS: A total of 5926 subjects who met the study's entry criteria were randomly selected from the urban and rural areas of Beijing and interviewed using standardized assessment tools, including the collection of basic socio-demographic and clinical data. All subjects fully cooperated in the interviews and readily disclosed all of the information. RESULTS: The prevalence of lifetime smoking was 35.9%; the rates for current mild and heavy smoking were 21.8% and 10.8%, respectively. An age of 24 years or above, male sex, married, divorced, separated or widowed marital status, relatively low level of education (less than college level), being employed, a relatively high monthly income (more than RMB500), rural abode, and having a psychiatric disorder were risk factors of current smoking. Both current mild and heavy smoking were significantly associated with alcohol dependence, and current heavy smoking was also associated with a history of a major depressive episode. CONCLUSIONS: The prevalence of smoking in the rural and urban areas of Beijing is unacceptably high. In addition to certain socio-demographic factors, smoking was associated with common psychiatric disorders. Nationwide surveys are warranted to further explore the prevalence of smoking in China. Effective strategies to reduce the high rate of smoking are also needed.

Prevalence and socio-demographic correlates of major depressive episode in rural and urban areas of Beijing, China.

OBJECTIVE: This study aimed to determine the 12-month and lifetime prevalence of major depressive episode (MDE) and their socio-demographic correlates in both the urban and rural areas of Beijing, China. METHODS: A total of 4767 adults were randomly selected and interviewed in Beijing using the Composite International Diagnostic Interview (CIDI 1.0). Basic socio-demographic and clinical data were collected during the interviews. RESULTS: The overall 12-month prevalence of MDE was 3.2%; 2.8% and 3.8% for men and women, respectively. The overall lifetime prevalence of MDE was 5.3%; 4.4% and 6.3% for men and women, respectively. Being older than 25 years of age was independently associated with increased risk of MDE. Sixteen point three percent of the subjects with lifetime MDE attempted suicide while the rate of suicide attempts was only 0.2% in subjects without MDE. The percentage of subjects with MDE who received any type of treatment from medical practitioners was 33.1%; of them, only 5.4% sought help from mental health professionals. CONCLUSIONS: National epidemiologic surveys are needed to further explore the prevalence of MDE in China. The low percentage of subjects treated for MDE constitutes a major public health problem that should be urgently addressed.