A comprehensive review on knowledge graphs for complex diseases.

In recent years, knowledge graphs (KGs) have gained a great deal of popularity as a tool for storing relationships between entities and for performing higher level reasoning. KGs in biomedicine and clinical practice aim to provide an elegant solution for diagnosing and treating complex diseases more efficiently and flexibly. Here, we provide a systematic review to characterize the state-of-the-art of KGs in the area of complex disease research. We cover the following topics: (1) knowledge sources, (2) entity extraction methods, (3) relation extraction methods and (4) the application of KGs in complex diseases. As a result, we offer a complete picture of the domain. Finally, we discuss the challenges in the field by identifying gaps and opportunities for further research and propose potential research directions of KGs for complex disease diagnosis and treatment.

Highly Efficient Single-Exciton Strong Coupling with Plasmons by Lowering Critical Interaction Strength at an Exceptional Point.

The single-exciton strong coupling with the localized plasmon mode (LPM) at room temperature is highly desirable for exploiting quantum technology. However, its realization has been a very low probability event due to the harsh critical conditions, severely compromising its application. Here, we present a highly efficient approach for achieving such a strong coupling by reducing the critical interaction strength at the exceptional point based upon the damping inhibition and matching of the coupled system, instead of enhancing the coupling strength to overcome the system's large damping. Experimentally, we compress the LPM's damping linewidth from about 45 nm to about 14 nm using a leaky Fabry-Perot cavity, a good match to the excitonic linewidth of about 10 nm. This method dramatically relaxes the harsh requirement in mode volume by more than an order of magnitude and allows a maximum direction angle of the exciton dipole relative to the mode field of up to around 71.9°, significantly improving the success rate of achieving the single-exciton strong coupling with LPMs from about 1% to about 80%.

Anomalous spontaneous emission dynamics at chiral exceptional points.

An open quantum system operated at the spectral singularities where dimensionality reduces, known as exceptional points (EPs), demonstrates distinguishing behavior from the Hermitian counterpart. Here, we present an analytical description of local density of states (LDOS) for microcavity featuring chiral EPs, and unveil the anomalous spontaneous emission dynamics from a quantum emitter (QE) due to the non-Lorentzian response of EPs. Specifically, we reveal that a squared Lorentzian term of LDOS contributed by chiral EPs can destructively interfere with the linear Lorentzian profile, resulting in the null Purcell enhancement to a QE with special transition frequency, which we call EP induced transparency. While for the case of constructive interference, the squared Lorentzian term can narrow the linewidth of Rabi splitting even below that of bare components, and thus significantly suppresses the decay of Rabi oscillation. Interestingly, we further find that an open microcavity with chiral EPs supports atom-photon bound states for population trapping and decay suppression in long-time dynamics. As applications, we demonstrate the advantages of microcavity operated at chiral EPs in achieving high-fidelity entanglement generation and high-efficiency single-photon generation. Our work unveils the exotic cavity quantum electrodynamics unique to chiral EPs, which opens the door for controlling light-matter interaction at the quantum level through non-Hermiticity, and holds great potential in building high-performance quantum-optics devices.

Fano effect induced giant and robust enhancement of photon correlations in cavity QED systems.

The Fano effect arising from the interference between two dissipation channels of the radiation continuum enables tuning of the photon statistics. Understanding the role of the Fano effect and exploiting it to achieve strong photon correlations are of both fundamental and applied significance. We present an analytical description of Fano-enhanced photon correlations based on cavity quantum electrodynamics to show that the Fano effect in atom-cavity systems can improve the degree of antibunching by over four orders of magnitude. The enhancement factors and the optimal conditions are explicitly given, and found to relate to the Fano parameter q. Remarkably, the Fano enhancement manifests robustness against the decoherence processes and can survive in the weak coupling regime. We expect our work to provide insight to tuning the photon statistics through the Fano effect, which offers a new, to the best of our knowledge, route to enhance the photon correlations, as well as the possibility of generating nonclassical light in a wider diversity of systems without the need of a strong light-matter interaction.

Cavity spectral-hole-burning to boost coherence in plasmon-emitter strong coupling systems.

Significant decoherence of the plasmon-emitter (i.e., plexcitonic) strong coupling systems hinders the progress towards their applications in quantum technology due to the unavoidable lossy nature of the plasmons. Inspired by the concept of spectral-hole-burning (SHB) for frequency-selective bleaching of the emitter ensemble, we propose 'cavity SHB' by introducing cavity modes with moderate quality factors to the plexcitonic system to boost its coherence. We show that the detuning of the introduced cavity mode with respect to the original plexcitonic system, which defines the location of the cavity SHB, is the most critical parameter. Simultaneously introducing two cavity modes of opposite detunings, the excited-state population of the emitter can be enhanced by 4.5 orders of magnitude within 300 fs, and the attenuation of the emitter's population can be slowed down by about 56 times. This theoretical proposal provides a new approach of cavity engineering to enhance the plasmon-emitter strong coupling systems' coherence, which is important for realistic hybrid-cavity design for applications in quantum technology.

A Robust Detection Algorithm for Infrared Maritime Small and Dim Targets.

Infrared maritime target detection is the key technology of maritime target search systems. However, infrared images generally have the defects of low signal-to-noise ratio and low resolution. At the same time, the maritime environment is complicated and changeable. Under the interference of islands, waves and other disturbances, the brightness of small dim targets is easily obscured, which makes them difficult to distinguish. This is difficult for traditional target detection algorithms to deal with. In order to solve these problems, through the analysis of infrared maritime images under a variety of sea conditions including small dim targets, this paper concludes that in infrared maritime images, small targets occupy very few pixels, often do not have any edge contour information, and the gray value and contrast values are very low. The background such as island and strong sea wave occupies a large number of pixels, with obvious texture features, and often has a high gray value. By deeply analyzing the difference between the target and the background, this paper proposes a detection algorithm (SRGM) for infrared small dim targets under different maritime background. Firstly, this algorithm proposes an efficient maritime background filter for the common background in the infrared maritime image. Firstly, the median filter based on the sensitive region selection is used to extract the image background accurately, and then the background is eliminated by image difference with the original image. In addition, this article analyzes the differences in gradient features between strong interference caused by the background and targets, proposes a small dim target extraction operator with two analysis factors that fit the target features perfectly and combines the adaptive threshold segmentation to realize the accurate extraction of the small dim target. The experimental results show that compared with the current popular small dim target detection algorithms, this paper has better performance for target detection in various maritime environments.

Theoretical Prediction on the New Types of Noble Gas Containing Anions OBONgO- and OCNNgO- (Ng = He, Ar, Kr and Xe).

The fluorine-less noble gas containing anions OBONgO- and OCNNgO- have been studied by correlated electronic structure calculation and density functional theory. The obtained energetics indicates that for Ng = Kr and Xe, these anions should be kinetically stable at low temperature. The molecular structures and electron density distribution suggests that these anions are stabilized by ion-induced dipole interactions with charges concentrated on the electronegative OBO and OCN groups. The current study shows that in addition to the fluoride ion, polyatomic groups with strong electronic affinities can also form stable noble gas containing anions of the type Y-…NgO.

Probing Thermal Stability of Proteins with Temperature Scanning Viscometer.

Thermal stability is essential for the understanding of protein stability and is a critical quality attribute of therapeutic biologics, including enzymes, fusion proteins, monoclonal antibodies, etc. The commonly used analytical methods, such as differential scanning calorimetry (DSC), differential scanning fluorimetry (DSF), and circular dichroism (CD), have their limitations in measuring protein thermal stability. Through this work, we described a novel method to probe the thermal stability of proteins in various formulations using a temperature scanning viscometer. The viscosity of the material was plotted against the temperature, and the peak in the first derivative of the viscosity versus temperature was shown to be related to the protein melting temperature. The measured melting temperature of bovine serum albumin (BSA) at a concentration of 1 mg/mL in phosphate buffer was 63 °C, which was close to the value of 64 °C obtained by DSC. The unfolding of BSA was confirmed using orthogonal techniques of second derivative ultraviolet-visible (UV-vis) spectroscopy and dynamic light scattering (DLS). This method was also able to reveal the microenvironment changes of proteins, including formulation effects. Other multiple domains proteins including lysozyme and IgG were also tested using this method and showed comparable melting temperatures with DSC. This work showed the feasibility of using a temperature scanning viscometer to measure the thermal stability of proteins in diverse formulation matrices with wider protein concentration ranges.

Association study between the TP53 Rs1042522G/C polymorphism and susceptibility to systemic lupus erythematosus in a Chinese Han population.

Tumour suppressor protein 53 (p53) plays a central role in apoptosis, cell proliferation and death. Previously studies found contribution of functional p53 Arg72Pro polymorphism (TP53 rs1042522G/C polymorphism) in the development of systemic lupus erythematosus (SLE) remains controversial. In this study, for the first time, we evaluated its association with SLE in a Chinese Han population. This case-control study enrolled 1470 SLE patients and 2283 healthy controls. The genotyping of TP53 rs1042522 polymorphism was determined by Sequenom Mass ARRAY technology. Statistical analysis was conducted by Chi-square test (χ 2 test). Odds ratio (OR) with 95% confidence interval (CI) was calculated using unconditional logistic regression with adjusting age and sex. Allele and genotype frequencies of TP53 rs1042522G/C polymorphism showed statistically significant difference between the SLE patients and the normal controls (C vs. G: OR = 0.89, 95% CI 0.89-0.97, p = 0.01; (GC + CC) vs. GG using recessive model: OR = 0.84, 95% CI 0.73-0.96, p = 0.01; GC vs. GG using co-dominant model: OR = 0.86, 95% CI 0.74-0.99, p = 0.04; CC vs. GG using co-dominant model: OR = 0.80, 95% CI 0.66-0.96, p = 0.02; GC vs. GG using co-dominant model: OR = 0.86, 95% CI 0.74-0.99, p = 0.02). In addition, there was weak association between discoid rash and distribution of TP53 rs1042522G/C polymorphism in SLE patients (C vs. G: OR = 1.25, 95% CI 1.00-1.55, p = 0.04; CC vs. GG using co-dominant model: OR = 1.54, 95% CI 1.10-2.36, p = 0.04). Our finding suggests a significant relationship between the TP53 rs1042522G/C polymorphism and SLE. TP53 rs1042522G/C polymorphism would be promising as an indicator of SLE as well as the therapeutic target if its functions and mechanisms could be further investigated.

The effectiveness of a comprehensive reminder system in the secondary prevention of hypertensive ischaemic stroke: randomized controlled trial protocol.

AIM: The aim of this study was to determine whether the Comprehensive Reminder System based on the Health Belief Model improves health belief, health behaviours, medication adherence and blood pressure control as a means of decreasing the rate of stroke recurrence among hypertensive ischaemic stroke. BACKGROUND: Hypertensive patients having experienced recent ischaemic strokes are at high risk for stroke recurrence. Several trials attempted to improve secondary stroke prevention via patient education, however, patient outcomes remained poor. Long-term follow-up studies regarding secondary stroke prevention are limited. DESIGN: A multi-centre, 12-month, assessor-blinded, parallel-group, randomized controlled longitudinal trial. METHODS: Hypertensive patients having experienced an ischaemic stroke are the target population. The intervention consists of health belief education, a calendar handbook, a weekly automated short-message service and four telephone follow-up interviews. Outcomes will be assessed at baseline and at 3, 6 and 12 months following discharge. The primary outcome is blood pressure control. The secondary outcomes include health belief, health behaviours and medication adherence. The clinical endpoint is the rate of stroke recurrence. DISCUSSION: Although many efforts to improve secondary stroke prevention have been undertaken, research indicates that improvements remain possible and warranted. This research protocol based on the Health Belief Model will improve our understanding of stroke education and transitional care needed in China and with the world-wide target population.

Microbiota transplantation restores normal fecal bile acid composition in recurrent Clostridium difficile infection.

Fecal microbiota transplantation (FMT) has emerged as a highly effective therapy for refractory, recurrent Clostridium difficile infection (CDI), which develops following antibiotic treatments. Intestinal microbiota play a critical role in the metabolism of bile acids in the colon, which in turn have major effects on the lifecycle of C. difficile bacteria. We hypothesized that fecal bile acid composition is altered in patients with recurrent CDI and that FMT results in its normalization. General metabolomics and targeted bile acid analyses were performed on fecal extracts from patients with recurrent CDI treated with FMT and their donors. In addition, 16S rRNA gene sequencing was used to determine the bacterial composition of pre- and post-FMT fecal samples. Taxonomic bacterial composition of fecal samples from FMT recipients showed rapid change and became similar to the donor after the procedure. Pre-FMT fecal samples contained high concentrations of primary bile acids and bile salts, while secondary bile acids were nearly undetectable. In contrast, post-FMT fecal samples contained mostly secondary bile acids, as did non-CDI donor samples. Therefore, our analysis showed that FMT resulted in normalization of fecal bacterial community structure and metabolic composition. Importantly, metabolism of bile salts and primary bile acids to secondary bile acids is disrupted in patients with recurrent CDI, and FMT corrects this abnormality. Since individual bile salts and bile acids have pro-germinant and inhibitory activities, the changes suggest that correction of bile acid metabolism is likely a major mechanism by which FMT results in a cure and prevents recurrence of CDI.

Characterization of Urinary N-Acetyltaurine as a Biomarker of Hyperacetatemia in Mice.

Acetate is an important metabolite in metabolic fluxes. Its presence in biological entities originates from both exogenous inputs and endogenous metabolism. Because the change in blood acetate level has been associated with both beneficial and adverse health outcomes, blood acetate analysis has been used to monitor the systemic status of acetate turnover. The present study examined the use of urinary N-acetyltaurine (NAT) as a marker to reflect the hyperacetatemic status of mice from exogenous inputs and endogenous metabolism, including triacetin dosing, ethanol dosing, and streptozotocin-induced diabetes. The results showed that triacetin dosing increased serum acetate and urinary NAT but not other N-acetylated amino acids in urine. The co-occurrences of increased serum acetate and elevated urinary NAT were also observed in both ethanol dosing and streptozotocin-induced diabetes. Furthermore, the renal cortex was determined as an active site for NAT synthesis. Overall, urinary NAT behaved as an effective marker of hyperacetatemia in three experimental mouse models, warranting further investigation into its application in humans.

MKG-GC: A multi-task learning-based knowledge graph construction framework with personalized application to gastric cancer.

Over the past decade, information for precision disease medicine has accumulated in the form of textual data. To effectively utilize this expanding medical text, we proposed a multi-task learning-based framework based on hard parameter sharing for knowledge graph construction (MKG), and then used it to automatically extract gastric cancer (GC)-related biomedical knowledge from the literature and identify GC drug candidates. In MKG, we designed three separate modules, MT-BGIPN, MT-SGTF and MT-ScBERT, for entity recognition, entity normalization, and relation classification, respectively. To address the challenges posed by the long and irregular naming of medical entities, the MT-BGIPN utilized bidirectional gated recurrent unit and interactive pointer network techniques, significantly improving entity recognition accuracy to an average F1 value of 84.5% across datasets. In MT-SGTF, we employed the term frequency-inverse document frequency and the gated attention unit. These combine both semantic and characteristic features of entities, resulting in an average Hits@ 1 score of 94.5% across five datasets. The MT-ScBERT integrated cross-text, entity, and context features, yielding an average F1 value of 86.9% across 11 relation classification datasets. Based on the MKG, we then developed a specific knowledge graph for GC (MKG-GC), which encompasses a total of 9129 entities and 88,482 triplets. Lastly, the MKG-GC was used to predict potential GC drugs using a pre-trained language model called BioKGE-BERT and a drug-disease discriminant model based on CNN-BiLSTM. Remarkably, nine out of the top ten predicted drugs have been previously reported as effective for gastric cancer treatment. Finally, an online platform was created for exploration and visualization of MKG-GC at https://www.yanglab-mi.org.cn/MKG-GC/.

Deterministic positioning and alignment of a single-molecule exciton in plasmonic nanodimer for strong coupling.

Experimental realization of strong coupling between a single exciton and plasmons remains challenging as it requires deterministic positioning of the single exciton and alignment of its dipole moment with the plasmonic fields. This study aims to combine the host-guest chemistry approach with the cucurbit[7]uril-mediated active self-assembly to precisely integrate a single methylene blue molecule in an Au nanodimer at the deterministic position (gap center of the nanodimer) with the maximum electric field (EFmax) and perfectly align its transition dipole moment with the EFmax, yielding a large spectral Rabi splitting of 116 meV for a single-molecule exciton-matching the analytical model and numerical simulations. Statistical analysis of vibrational spectroscopy and dark-field scattering spectra confirm the realization of the single exciton strong coupling at room temperature. Our work may suggest an approach for achieving the strong coupling between a deterministic single exciton and plasmons, contributing to the development of room-temperature single-qubit quantum devices.

A gene signature linked to fibroblast differentiation for prognostic prediction of mesothelioma.

BACKGROUND: Malignant mesothelioma is a type of infrequent tumor that is substantially related to asbestos exposure and has a terrible prognosis. We tried to produce a fibroblast differentiation-related gene set for creating a novel classification and prognostic prediction model of MESO. METHOD: Three databases, including NCBI-GEO, TCGA, and MET-500, separately provide single-cell RNA sequencing data, bulk RNA sequencing profiles of MESO, and RNA sequencing information on bone metastatic tumors. Dimensionality reduction and clustering analysis were leveraged to acquire fibroblast subtypes in the MESO microenvironment. The fibroblast differentiation-related genes (FDGs), which were associated with survival and subsequently utilized to generate the MESO categorization and prognostic prediction model, were selected in combination with pseudotime analysis and survival information from the TCGA database. Then, regulatory network was constructed for each MESO subtype, and candidate inhibitors were predicted. Clinical specimens were collected for further validation. RESULT: A total of six fibroblast subtypes, three differentiation states, and 39 FDGs were identified. Based on the expression level of FDGs, three MESO subtypes were distinguished in the fibroblast differentiation-based classification (FDBC). In the multivariate prognostic prediction model, the risk score that was dependent on the expression level of several important FDGs, was verified to be an independently effective prognostic factor and worked well in internal cohorts. Finally, we predicted 24 potential drugs for the treatment of MESO. Moreover, immunohistochemical staining and statistical analysis provided further validation. CONCLUSION: Fibroblast differentiation-related genes (FDGs), especially those in low-differentiation states, might participate in the proliferation and invasion of MESO. Hopefully, the raised clinical subtyping of MESO would provide references for clinical practitioners.

A 10-year mono-center study on patients with burns ≥70% TBSA: prediction model construction and multi-center validation: retrospective cohort.

BACKGROUND: Burn injuries with ≥70% total body surface area (TBSA) are especially acute and life-threatening, leading to severe complications and terrible prognosis, while a powerful model for prediction of overall survival (OS) is lacked. The objective of this study is to identify prognostic factors for the OS of patients with burn injury ≥70% TBSA, construct and validate a feasible predictive model. MATERIALS AND METHODS: Patients diagnosed with burns ≥70% TBSA admitted and treated between 2010 and 2020 in our hospital were included. A cohort of the patients from the Kunshan explosion were assigned as the validation set. The Chi-square test and K-M survival analysis were conducted to identify potential predictors for OS. Then, multi-variate Cox regression analysis was performed to identify the independent factors. Afterwards, we constructed a nomogram to predict OS probability. Finally, the Kunshan cohort was applied as an external validation set. RESULTS: Gender, the percentage of third- and fourth-degree burn as well as organ dysfunction were identified as significant independent factors. A nomogram only based on the factors of the individuals was built and evidenced to have promising predictive accuracy, accordance, and discrimination by both internal and external validation. CONCLUSIONS: This study recognized significant influencing factors for the OS of patients with burns ≥70% TBSA. Furthermore, our nomogram proved to be an effective tool for doctors to quickly evaluate patients' outcomes and make appropriate clinical decisions at an early stage of treatment.

High-throughput and separating-free phenotyping method for on-panicle rice grains based on deep learning.

Rice is a vital food crop that feeds most of the global population. Cultivating high-yielding and superior-quality rice varieties has always been a critical research direction. Rice grain-related traits can be used as crucial phenotypic evidence to assess yield potential and quality. However, the analysis of rice grain traits is still mainly based on manual counting or various seed evaluation devices, which incur high costs in time and money. This study proposed a high-precision phenotyping method for rice panicles based on visible light scanning imaging and deep learning technology, which can achieve high-throughput extraction of critical traits of rice panicles without separating and threshing rice panicles. The imaging of rice panicles was realized through visible light scanning. The grains were detected and segmented using the Faster R-CNN-based model, and an improved Pix2Pix model cascaded with it was used to compensate for the information loss caused by the natural occlusion between the rice grains. An image processing pipeline was designed to calculate fifteen phenotypic traits of the on-panicle rice grains. Eight varieties of rice were used to verify the reliability of this method. The R2 values between the extraction by the method and manual measurements of the grain number, grain length, grain width, grain length/width ratio and grain perimeter were 0.99, 0.96, 0.83, 0.90 and 0.84, respectively. Their mean absolute percentage error (MAPE) values were 1.65%, 7.15%, 5.76%, 9.13% and 6.51%. The average imaging time of each rice panicle was about 60 seconds, and the total time of data processing and phenotyping traits extraction was less than 10 seconds. By randomly selecting one thousand grains from each of the eight varieties and analyzing traits, it was found that there were certain differences between varieties in the number distribution of thousand-grain length, thousand-grain width, and thousand-grain length/width ratio. The results show that this method is suitable for high-throughput, non-destructive, and high-precision extraction of on-panicle grains traits without separating. Low cost and robust performance make it easy to popularize. The research results will provide new ideas and methods for extracting panicle traits of rice and other crops.

Microstructure and Efflorescence Resistance of Metakaolin Geopolymer Modified by 5A Zeolite.

In order to reduce the degree of efflorescence in alkali-activated metakaolin geopolymers, a modified 5A zeolite with cation-exchange properties was used to reduce the content of free alkali metal cations in the geopolymer. This work aims to investigate the effect of different dosages of modified 5A zeolite on the microstructure and properties of geopolymer by using compressive strength testing, pore structure analysis (BET), and SEM-EDS. The cation content in the leachate was evaluated using inductively coupled plasma atomic emission spectrometry (ICP-OES). The efflorescence area of the geopolymer was calculated using Image Pro Plus (IPP) software to evaluate the effect of modified 5A zeolite on the degree of efflorescence of the geopolymer and to reveal the effect of modified 5A zeolite on the migration patterns of Na+ and Ca2+ in the geopolymer. The results showed that modified 5A zeolite with a 4 wt.% content could optimize the pore structure and enhance the mechanical properties of MK geopolymer through internal curing and micro-aggregate effects, which could also exchange cations with the pore solution to form (N, C)-A-S-H gels. The Na+ leaching was reduced by 19.4%, and the efflorescence area of the MK geopolymer was reduced by 57.3%.

Overcoming slow removal efficiency-induced highly toxic I-DBPs in water by oxygen vacancies enriched invasive plant biochar catalyst: Experimental and theoretical studies.

Developing effective and safe catalysts operated in the in-depth removal of iodinated X-ray contrast media is important for overcoming slow removal efficiency-induced highly toxic iodine-replaced disinfection byproducts (I-DBPs). In this study, a novel oxygen vacancies enriched heterogeneous biochar catalyst (Mo-Co-ECM) from the invasive plant was synthesized by a facile one-step hydrothermal carbonization method and used for the in-depth removal of iohexol (IOH) by the activation of peroxymonosulfate (PMS). The results indicated that after adding PMS for 3 min, the removal efficiency of IOH in Mo-Co-ECM/PMS system reached 100% and exhibited a superior degradation efficiency compared to Co-ECM/PMS and ECM/PMS system. Only nine I-DBPs were found during the degradation, which were dominated by small molecules compounds (MW<400). The in-depth degradation suppresses the formation of the toxic intermediates. The density functional theory and electron spin resonance showed that due to the existence of Mo and oxygen vacancies, the electron transfer ability was improved, which accelerated the cycle of Co3+/Co2+, so as to enhance the catalytic activity of Mo-Co-ECM/PMS system. This study is expected to provide a general way for decreasing the production of toxic intermediates during the advanced oxidation of contaminants, meanwhile recovering resources.

[Effect of catgut implantation on macrophage CD68, tumor necrosis factor-α and interleukin-1ß in "Zusanli" (ST 36) region of rats].

OBJECTIVE: To observe the expression of local macrophages and related cytokines tumor necrosis factor-α (TNF-α) and interleukin-1ß (IL-1ß) after catgut implantation in "Zusanli"(ST 36) in rats, so as to explore its underlying mechanisms in inducing therapeutic effect. METHODS: A total of 110 male SD rats were randomly divided into blank control group (n=10), catgut embedding (CE) group (n=50), and sham CE group (n=50). The CE and sham CE groups were randomly divided into 8 h, 3 d, 7 d, 14 d and 21 d subgroups after the intervention (n=10 in each time point group). Rats of the CE group were uniformly subjected into catgut embedding at ST36 once, and those of the sham CE group received embedding needle puncture at ST36 without catgut retention, and the blank control group was only grasped and fixed without other treatments. Tissues from the ST36 area in each group were collected at the corresponding time points, and the expression of CD68 in macrophages in the acupoint area was detected by immunofluorescence, the contents of TNF-α and IL-1ß in the acupoint area were detected by ELISA. RESULTS: Following catgut embedment at ST36, the contents of TNF-α and IL-1ß, and macrophage CD68 expression level began to increase at 8 h, peaked at 3 d, and then gradually decreased at 7, 14, and 21 d, being still higher in the CE group than in the blank control group at 21 d (P<0.05). Compared with the blank control group, the contents of TNF-α and IL-1ß, and macrophage CD68 expression were significantly increased at 8 h, and 3, 7, 14 and 21 d in the CE group (P<0.05). Following sham CE at ST36, the content of TNF-α at 8 h and 3 d, IL-1ß at 8 h and 3, 7 and 14 d, and expression of CD68 at 8 h were significantly increased in comparison with the blank control group (P<0.05). Comparison between the CE and sham CE groups showed that the contents of IL-1ß at 3, 7, 14 and 21 d, and contents of TNF-α，CD68 expression at 8 h, and 3, 7, 14 and 21 d were significantly higher in the CE group than in the sham CE group (P<0.05). CONCLUSION: Catgut embedding at ST36 can induce an increase levels of inflammatory cytokines TNF-α, IL-1ß and macrophage CD68 in the local microenvironment in rats, which may contribute to its functions in initiating therapeutic effect.