Anti-osteoporosis effect of bioactives in edible medicinal plants: a comprehensive review.

Current treatments for osteoporosis include a calcium-rich diet, adequate exercise, and medication. Many synthetic drugs, although fast-acting, can cause a range of side effects for patients when taken over a long period, such as irritation of the digestive tract and a burden on the kidneys. As the world's population ages, the prevalence of osteoporosis is increasing, and the development of safe and effective treatments is urgently needed. Active compounds in edible and medicinal homologous plants have been used for centuries to improve bone quality. It is possible to employ them as dietary supplements to prevent osteoporosis. In this review, we analyze the influencing factors of osteoporosis and systematically summarize the research progress on the anti-osteoporosis effects of active compounds in edible and medicinal homologous plants. The literature suggests that some naturally occurring active compounds in edible and medicinal homologous plants can inhibit bone loss, prevent the degeneration of bone cell microstructure, and reduce bone fragility through alleviating oxidative stress, regulating autophagy, anti-inflammation, improving gut flora, and regulating estrogen level with little side effects. Our review provides useful guidance for the use of edible and medicinal homologous plants and the development of safer novel anti-osteoporosis dietary supplements.

Evaluation of the Quality of Management Guidelines for Children and Adolescents With Autism Spectrum Disorder.

OBJECTIVE: To systematically assess the quality of management guidelines for children and adolescents with autism spectrum disorder, analyze key management recommendation differences and causes among guidelines, and provide better guideline assessments for clinical workers. METHODS: Clinical guidelines for managing children and adolescents with autism were systematically retrieved from a database. Four reviewers independently evaluated the guidelines using the assessment guideline tool, Appraisal of Guidelines for Research and Evaluation II (AGREE II), and the intra-group correlation coefficient (ICC) was used to measure the consistency of the assessment guidelines among the four reviewers and the differences and reasons for the recommendations and supporting evidence were compared and analyzed. RESULTS: A total of ten management guidelines for children and adolescents with autism spectrum disorder published from 2014 to 2022 were included in this study, with high overall agreement between raters (range of intra-group correlation coefficients: 53.3% ∼ 85.0%), and areas with better median scores and ranges in Protocol II were as follows: domain 1 (scope and purpose, median = 86.1%, 59.7%-98.6%), Domain 4 (clarity of statements, median = 88.2%, 38.9%-100.0%) and domain 6 (independence of editors, median = 71.9%, 0.0%-100.0%). Among the ten guidelines the guidelines published by the Scott Intercollegiate Guidelines Network in 2016 and by the National Institute for health and care excellence in 2021 scored high and were recommended for adoption, 88.7%, 84.9%, respectively. CONCLUSION: There is considerable variation between the quality of guidelines for the management of children and adolescents with autism spectrum disorders.

IRIME: Mitigating exploitation-exploration imbalance in RIME optimization for feature selection.

Rime optimization algorithm (RIME) encounters issues such as an imbalance between exploitation and exploration, susceptibility to local optima, and low convergence accuracy when handling problems. This paper introduces a variant of RIME called IRIME to address these drawbacks. IRIME integrates the soft besiege (SB) and composite mutation strategy (CMS) and restart strategy (RS). To comprehensively validate IRIME's performance, IEEE CEC 2017 benchmark tests were conducted, comparing it against many advanced algorithms. The results indicate that the performance of IRIME is the best. In addition, applying IRIME in four engineering problems reflects the performance of IRIME in solving practical problems. Finally, the paper proposes a binary version, bIRIME, that can be applied to feature selection problems. bIRIMR performs well on 12 low-dimensional datasets and 24 high-dimensional datasets. It outperforms other advanced algorithms in terms of the number of feature subsets and classification accuracy. In conclusion, bIRIME has great potential in feature selection.

Extraction and characterization of hepatoprotective polysaccharides from Anoectochilus roxburghii against CCl4-induced liver injury via regulating lipid metabolism and the gut microbiota.

Anoectochilus roxburghii polysaccharides exhibit notable hepatoprotective effects, but the underlying substance basis and mechanisms remain unknown. In this study, four new polysaccharides named ARP-1a, ARP-1b, ARP-2a and ARP-2b, were isolated from A. roxburghii. Their structural characteristics were systematically analyzed using HPGPC, HPLC, GC-MS, IR and NMR analysis. ARP-1a, the leading polysaccharide isolated from A. roxburghii, was further evaluated for its hepatoprotective effects on acute liver injury mice induced by CCl4. ARP-1a significantly reduced the serum ALT, AST, TNF-α, IL-1ß and IL-6 levels, liver MDA content, and increased the SOD and CAT activities and GSH level in liver. H&E staining revealed that ARP-1a pretreatment could markedly relieve liver injury. Further mechanism exploration indicated that ARP-1a could relieve CCl4-induced oxidative damage through activating the Nrf2 signaling. In addition, metabolomics, lipidomics and 16S rRNA amplicon sequencing were used to elucidate the underlying mechanisms of ARP-1a. Multi-omics analysis indicated that ARP-1a exerted hepatoprotective effect against CCl4-induced acute liver injury by regulating lipid metabolism and modulating the gut microbiota. In conclusion, the above results suggest that ARP-1a can be considered a promising and safe candidate for hepatoprotective drug, as well as a potential prebiotic for maintaining intestinal homeostasis and promoting human intestinal health.

Environment random interaction of rime optimization with Nelder-Mead simplex for parameter estimation of photovoltaic models.

As countries attach importance to environmental protection, clean energy has become a hot topic. Among them, solar energy, as one of the efficient and easily accessible clean energy sources, has received widespread attention. An essential component in converting solar energy into electricity are solar cells. However, a major optimization difficulty remains in precisely and effectively calculating the parameters of photovoltaic (PV) models. In this regard, this study introduces an improved rime optimization algorithm (RIME), namely ERINMRIME, which integrates the Nelder-Mead simplex (NMs) with the environment random interaction (ERI) strategy. In the later phases of ERINMRIME, the ERI strategy serves as a complementary mechanism for augmenting the solution space exploration ability of the agent. By facilitating external interactions, this method improves the algorithm's efficacy in conducting a global search by keeping it from becoming stuck in local optima. Moreover, by incorporating NMs, ERINMRIME enhances its ability to do local searches, leading to improved space exploration. To evaluate ERINMRIME's optimization performance on PV models, this study conducted experiments on four different models: the single diode model (SDM), the double diode model (DDM), the three-diode model (TDM), and the photovoltaic (PV) module model. The experimental results show that ERINMRIME reduces root mean square error for SDM, DDM, TDM, and PV module models by 46.23%, 59.32%, 61.49%, and 23.95%, respectively, compared with the original RIME. Furthermore, this study compared ERINMRIME with nine improved classical algorithms. The results show that ERINMRIME is a remarkable competitor. Ultimately, this study evaluated the performance of ERINMRIME across three distinct commercial PV models, while considering varying irradiation and temperature conditions. The performance of ERINMRIME is superior to existing similar algorithms in different irradiation and temperature conditions. Therefore, ERINMRIME is an algorithm with great potential in identifying and recognizing unknown parameters of PV models.

Mtnr1b deletion disrupts placental angiogenesis through the VEGF signaling pathway leading to fetal growth restriction.

The placenta, as a "transit station" between mother and fetus, has functions delivering nutrients, excreting metabolic wastes and secreting hormones. A healthy placenta is essential for fetal growth and development while the melatonergic system seems to play a critical physiological role in this organ since melatonin, its synthetic enzymes and receptors are present in the placenta. In current study, Mtnr1a and Mtnr1b knockout mice were constructed to explore the potential roles of melatonergic system played on the placental function and intrauterine growth retardation (IUGR). The result showed that Mtnr1a knockout had little effect on placental function while Mtnr1b knockout reduced placental efficiency and increased IUGR. Considering the extremely high incidence of IURG in sows, the pregnant sows were treated with melatonin. This treatment reduced the incidence of IUGR. All the evidence suggests that the intact melatonergic system in placenta is required for its function. Mechanistical studies uncovered that Mtnr1b knockout increased placental oxidative stress and apoptosis but reduced the angiogenesis. The RNA sequencing combined with histochemistry study identified the reduced angiogenesis and placental vascular density in Mtnr1b knockout mice. These alterations were mediated by the disrupted STAT3/VEGFR2/PI3K/AKT pathway, i.e., Mtnr1b knockout reduced the phosphorylation of STAT3 which is the promotor of VEGFR2. The downregulated VEGFR2 and its downstream elements of PI3K and AKT expressions, then, jeopardizes the angiogenesis and placental development.

Optimization of enzyme-assisted microwave extraction, structural characterization, antioxidant activity and in vitro protective effect against H2O2-induced damage in HepG2 cells of polysaccharides from roots of Rubus crataegifolius Bunge.

In this study, an enzyme-assisted microwave extraction process was obtained by response surface method of polysaccharide from roots of Rubus crataegifolius Bunge. The optimized extraction process was as follow: enzyme dosage 2 %, enzymatic time was 3.6 h, enzymatic pH 4.9, and microwave time 4.7 min, with the extraction yield of 9.07 %. Four homogeneous polysaccharides (RCP-1, RCP-3, RCP-4 and RCP-5) were purified through column chromatography. Four polysaccharides have the relative higher molecular weights of 1.70 × 106 Da, 5.56 × 106 Da, 4.97 × 106 Da, and 9.80 × 106 Da and mainly consisted of GluN, GluA, Glu, Gal and Arab. FT-IR and NMR spectral analysis confirmed that the purified polysaccharides were polypyranose containing α- and ß-glycosidic bonds. RCP - 1 has a relative high crystallinity. Four purified polysaccharides contained triple helical conformations, and have good antioxidant activities. Among the purified polysaccharides, RCP - 1 was found to reduce the oxidative cell damage induced by H2O2 through increasing of cell viability, inhibition of AST and ALT levels, ROS production and cell apoptosis, increasing of the activities of antioxidative enzymes, as well as reduction of MDA content. Our findings would provide a foundation for purified polysaccharides efficient extraction and demonstrated that the polysaccharides from R. crataegifolius roots could be a promising hepatoprotective agent.

Improved Latin hypercube sampling initialization-based whale optimization algorithm for COVID-19 X-ray multi-threshold image segmentation.

Image segmentation techniques play a vital role in aiding COVID-19 diagnosis. Multi-threshold image segmentation methods are favored for their computational simplicity and operational efficiency. Existing threshold selection techniques in multi-threshold image segmentation, such as Kapur based on exhaustive enumeration, often hamper efficiency and accuracy. The whale optimization algorithm (WOA) has shown promise in addressing this challenge, but issues persist, including poor stability, low efficiency, and accuracy in COVID-19 threshold image segmentation. To tackle these issues, we introduce a Latin hypercube sampling initialization-based multi-strategy enhanced WOA (CAGWOA). It incorporates a COS sampling initialization strategy (COSI), an adaptive global search approach (GS), and an all-dimensional neighborhood mechanism (ADN). COSI leverages probability density functions created from Latin hypercube sampling, ensuring even solution space coverage to improve the stability of the segmentation model. GS widens the exploration scope to combat stagnation during iterations and improve segmentation efficiency. ADN refines convergence accuracy around optimal individuals to improve segmentation accuracy. CAGWOA's performance is validated through experiments on various benchmark function test sets. Furthermore, we apply CAGWOA alongside similar methods in a multi-threshold image segmentation model for comparative experiments on lung X-ray images of infected patients. The results demonstrate CAGWOA's superiority, including better image detail preservation, clear segmentation boundaries, and adaptability across different threshold levels.

Hyaluronated nanohydroxyapatite responsively released from injectable hydrogels for targeted therapy of melanoma.

Nanohydroxyapatite (nHAp) has attracted significant attention for its tumor suppression and tumor microenvironment modulation capabilities. However, a strong tendency to aggregate greatly affects its anti-tumor efficiency. To address this issue, a hydrogel platform consisting of thiolated hyaluronic acid (HA-SH) modified nanohydroxyapatite (nHAp-HA) and HA-SH was developed for sustained delivery of nHAp for melanoma therapy. The hydrophilic and negatively charged HA-SH significantly improved the size dispersion and stability of nHAp in aqueous media while conferring nHAp targeting effects. Covalent sulfhydryl self-cross-linking between HA-SH and nHAp-HA groups ensured homogeneous dispersion of nHAp in the matrix material. Meanwhile, the modification of HA-SH conferred the targeting properties of nHAp and enhanced cellular uptake through the HA/CD44 receptor. The hydrogel platform could effectively reduce the aggregation of nHAp and release nHAp in a sustained and orderly manner. Antitumor experiments showed that the modified nHAp-HA retained the tumor cytotoxicity of nHAp in vitro and inhibited the growth of highly malignant melanomas up to 78.6% while being able to induce the differentiation of macrophages to the M1 pro-inflammatory and antitumor phenotype. This study will broaden the application of nanohydroxyapatite in tumor therapy.

The Impact of the COVID-19 Pandemic on Orthodontic Adult Patients' Characteristics and Decision on Orthodontic Appliance.

Purpose: There is an overall paucity of data examining the specific details of orthodontic patients' patterns or orthodontic service disruptions possibly influenced by COVID-19 pandemic. Therefore, this study aimed to explore the impact of the COVID-19 pandemic on orthodontic clinic disruption regarding the change in adult patients' characteristics and decisions of orthodontic treatment devices. Patients and Methods: A retrospective sample of 311 patients receiving orthodontic treatment from 2018 to 2022 were collected and divided into two groups: before (n = 167) and during (n = 144) the COVID-19 pandemic. Demographics, dental indices, the index of complexity outcome and need (ICON), and the degree of treatment difficulty were analyzed. Results: There were fewer students among patients during the COVID-19 pandemic than before (24.5% versus 35.9%, P = 0.036). Compared with patients before the pandemic, more patients selected ceramic brackets or Invisalign during the pandemic (P = 0.022). There were higher percentage of class I dental malocclusions among patients during than before the COVID-19 pandemic (P = 0.044). Moreover, the ICON score and the score of the degree of treatment difficulty were both significantly lower for patients during than before the COVID-19 pandemic (63.9±14.0 versus 58.3±15.3, P=0.001 and 7.4±2.6 versus 6.8±2.6, P=0.049, respectively). Conclusion: The COVID-19 pandemic influenced the characteristics and decisions of orthodontic patients. Those who still came to the orthodontic clinic despite the COVID-19 outbreak may have been those with less malocclusion severity and treatment difficulty. Besides, during the time of covid-19 pandemic, more patients chose ceramic bracket and Invisalign as their orthodontic treatment device rather than conventional or self-ligating metal brackets.

A global dataset of terrestrial evapotranspiration and soil moisture dynamics from 1982 to 2020.

Quantifying terrestrial evapotranspiration (ET) and soil moisture dynamics accurately is crucial for understanding the global water cycle and surface energy balance. We present a novel, long-term dataset of global ET and soil moisture derived from the newly developed Simple Terrestrial Hydrosphere model, version 2 (SiTHv2). This ecohydrological model, driven by multi-source satellite observations and hydrometeorological variables from reanalysis data, provides daily global ET-related estimates (e.g., total ET, plant transpiration, soil evaporation, intercepted evaporation) and three-layer soil moisture dynamics at a 0.1° spatial resolution. Validation with in-situ measurements and comparisons with mainstream global ET and soil moisture products demonstrate robust performance of SiTHv2 in both magnitude and temporal dynamics of ET and soil moisture at multiple scales. The comprehensive water path characterization in the SiTHv2 model makes this seamless dataset particularly valuable for studies requiring synchronized water budget and vegetation response to water constraints. With its long-term coverage and high spatiotemporal resolution, the SiTHv2-derived ET and soil moisture product will be suitable to support analyses related to the hydrologic cycle, drought assessment, and ecosystem health.

Enhanced differential evolution algorithm for feature selection in tuberculous pleural effusion clinical characteristics analysis.

Tuberculous pleural effusion poses a significant threat to human health due to its potential for severe disease and mortality. Without timely treatment, it may lead to fatal consequences. Therefore, early identification and prompt treatment are crucial for preventing problems such as chronic lung disease, respiratory failure, and death. This study proposes an enhanced differential evolution algorithm based on colony predation and dispersed foraging strategies. A series of experiments conducted on the IEEE CEC 2017 competition dataset validated the global optimization capability of the method. Additionally, a binary version of the algorithm is introduced to assess the algorithm's ability to address feature selection problems. Comprehensive comparisons of the effectiveness of the proposed algorithm with 8 similar algorithms were conducted using public datasets with feature sizes ranging from 10 to 10,000. Experimental results demonstrate that the proposed method is an effective feature selection approach. Furthermore, a predictive model for tuberculous pleural effusion is established by integrating the proposed algorithm with support vector machines. The performance of the proposed model is validated using clinical records collected from 140 tuberculous pleural effusion patients, totaling 10,780 instances. Experimental results indicate that the proposed model can identify key correlated indicators such as pleural effusion adenosine deaminase, temperature, white blood cell count, and pleural effusion color, aiding in the clinical feature analysis of tuberculous pleural effusion and providing early warning for its treatment and prediction.

Porous gradient hydrogel promotes skin regeneration by angiogenesis.

The skin has a multilayered structure, and deep-seated injuries are exposed to external microbial invasion and in vivo microenvironmental destabilization. Here, a bilayer bionic skin scaffold (Bilayer SF) was developed based on methacrylated sericin protein to mimic the skin's multilayered structure and corresponding functions. The outer layer (SF@TA), which mimics the epidermal layer, was endowed with the function of resisting external bacterial and microbial invasion using a small pore structure and bio-crosslinking with tannic acid (TA). The inner layer (SF@DA@Gel), which mimics the dermal layer, was used to promote cellular growth using a large pore structure and introducing dopamine (DA) to regulate the wound microenvironment. This Bilayer SF showed good mechanical properties and structural stability, satisfactory antioxidant and promote cell proliferation and migration abilities. In vitro studies confirmed the antimicrobial properties of the outer layer and the pro-angiogenic ability of the inner layer. In vivo animal studies demonstrated that the bilayer scaffolds promoted collagen deposition, neovascularization, and marginal hair follicle formation, which might be a promising new bionic skin scaffold.

Analyzing greenhouse gas emissions and influencing factors of 247 actual wastewater treatment plants in China using emission factor and operational data integrated methods (ODIM).

In response to China's policies on pollution control and carbon emission (CE) reductions, more stringent regulations have been implemented to evaluate CE in wastewater treatment facilities. In this study, we have analyzed CE from China's wastewater treatment plants (WWTPs) and influencing factor. Emission factor (EF) and operational data integrated methods (ODIM) were utilized to measure emissions, using data collected from 247 WWTPs over a 1-year period across seven regions in China. The average CE intensity was 0.45 kgCO2-eq/m3, affected by region, season, influent water quality, treatment processes, effluent discharge standards, and facilities. The scale effect was obvious only in the range of 2 × 105 m3/day. Underground WWTPs exhibited significantly higher CE compared to aboveground WWTPs. In summary, the assessment of CE in 247 actual WWTPs not only identifies emission reduction potential but also provides a scientific basis for formulating targeted emission reduction measures.

Photocatalytic toluene oxidation with nickel-mediated cascaded active units over Ni/Bi2WO6 monolayers.

Adsorption and activation of C-H bonds by photocatalysts are crucial for the efficient conversion of C-H bonds to produce high-value chemicals. Nevertheless, the delivery of surface-active oxygen species for C-H bond oxygenation inevitably needs to overcome obstacles due to the separated active centers, which suppresses the catalytic efficiency. Herein, Ni dopants are introduced into a monolayer Bi2WO6 to create cascaded active units consisting of unsaturated W atoms and Bi/O frustrated Lewis pairs. Experimental characterizations and density functional theory calculations reveal that these special sites can establish an efficient and controllable C-H bond oxidation process. The activated oxygen species on unsaturated W are readily transferred to the Bi/O sites for C-H bond oxygenation. The catalyst with a Ni mass fraction of 1.8% exhibits excellent toluene conversion rates and high selectivity towards benzaldehyde. This study presents a fascinating strategy for toluene oxidation through the design of efficient cascaded active units.

Utilize multi-metabolic parameters as determinants for prediction of skeletal muscle mass quality in elderly type2 diabetic Chinese patients.

BACKGROUND: Sarcopenia, an age-related disorder characterized by loss of skeletal muscle mass and function, is recently recognized as a complication in elderly patients with type 2 diabetes mellitus (T2DM). Skeletal muscles play a crucial role in glycemic metabolism, utilizing around 80% of blood glucose. Accordingly, we aimed to explore the relationship between glucose metabolism and muscle mass in T2DM. METHODS: We employed the AWGS 2019 criteria for diagnosing low muscle mass and 1999 World Health Organization (WHO) diabetes diagnostic standards. This study included data of 191 individuals aged 60 and above with T2DM of Shanghai Pudong Hospital from November 2021 to November 2022. Fasting C-peptide (FPCP), fasting plasma glucose (FPG), 2-hour postprandial plasma glucose (PPG) and postprandial 2-hour C-peptide (PPCP), glycated hemoglobin A1c (HbA1c), glycated albumin (GA), serum lipids spectrum, renal and hepatic function, hemoglobin, and hormone were measured. Based on the findings of univariate analysis, logistic regression and receiver operating characteristic (ROC) curves were established. RESULTS: Participants with low muscle mass had significantly lower alanine and aspartate aminotransferase, and both FPCP and PPCP levels (P < 0.05). Compared with those without low muscle mass, low muscle mass group had significantly higher FPG, HbA1c, GA levels (P < 0.05). Body fat (BF, OR = 1.181) was an independent risk factor for low muscle mass. PPCP (OR = 0.497), BMI (OR = 0.548), and female (OR = 0.050) were identified as protective factors for low skeletal muscle. The AUC of BMI was the highest, followed by the PPCP, gender and BF (0.810, 0.675, 0.647, and 0.639, respectively), and the AUC of the combination of the above four parameters reached 0.895. CONCLUSIONS: In this cross-sectional study, BMI, Female, and PPCP associated with T2DM were protective factors for low muscle mass. BF was associated with T2DM and risk factor for low muscle mass.

Dual roles of dopaminergic pathways in olfactory learning and memory in the oriental fruit fly, Bactrocera dorsalis.

Dopamine (DA) is a key regulator of associative learning and memory in both vertebrates and invertebrates, and it is widely believed that DA plays a key role in aversive conditioning in invertebrates. However, the idea that DA is involved only in aversive conditioning has been challenged in recent studies on the fruit fly (Drosophila melanogaster), ants and crabs, suggesting diverse functions of DA modulation on associative plasticity. Here, we present the results of DA modulation in aversive olfactory conditioning with DEET punishment and appetitive olfactory conditioning with sucrose reward in the oriental fruit fly, Bactrocera dorsalis. Injection of DA receptor antagonist fluphenazine or chlorpromazine into these flies led to impaired aversive learning, but had no effect on the appetitive learning. DA receptor antagonists impaired both aversive and appetitive long-term memory retention. Interestingly, the impairment on appetitive memory was rescued not only by DA but also by octopamine (OA). Blocking the OA receptors also impaired the appetitive memory retention, but this impairment could only be rescued by OA, not by DA. Thus, we conclude that in B. dorsalis, OA and DA pathways mediate independently the appetitive and aversive learning, respectively. These two pathways, however, are organized in series in mediating appetitive memory retrieval with DA pathway being at upstream. Thus, OA and DA play dual roles in associative learning and memory retrieval, but their pathways are organized differently in these two cognitive processes - parallel organization for learning acquisition and serial organization for memory retrieval.

Advancing forensic-based investigation incorporating slime mould search for gene selection of high-dimensional genetic data.

Modern medicine has produced large genetic datasets of high dimensions through advanced gene sequencing technology, and processing these data is of great significance for clinical decision-making. Gene selection (GS) is an important data preprocessing technique that aims to select a subset of feature information to improve performance and reduce data dimensionality. This study proposes an improved wrapper GS method based on forensic-based investigation (FBI). The method introduces the search mechanism of the slime mould algorithm in the FBI to improve the original FBI; the newly proposed algorithm is named SMA_FBI; then GS is performed by converting the continuous optimizer to a binary version of the optimizer through a transfer function. In order to verify the superiority of SMA_FBI, experiments are first executed on the 30-function test set of CEC2017 and compared with 10 original algorithms and 10 state-of-the-art algorithms. The experimental results show that SMA_FBI is better than other algorithms in terms of finding the optimal solution, convergence speed, and robustness. In addition, BSMA_FBI (binary version of SMA_FBI) is compared with 8 binary algorithms on 18 high-dimensional genetic data from the UCI repository. The results indicate that BSMA_FBI is able to obtain high classification accuracy with fewer features selected in GS applications. Therefore, SMA_FBI is considered an optimization tool with great potential for dealing with global optimization problems, and its binary version, BSMA_FBI, can be used for GS tasks.

Anti-inflammatory and immunoregulatory effects of colistin sulphate on human PBMCs.

In previous studies, CST has been identified as having an immunostimulatory effect on Caenorhabditis elegans and macrophage of rats. Here, we further investigated its immunomodulatory effects on human peripheral blood mononuclear cells (PBMCs). LPS-stimulated PBMCs inflammatory model was established. Flow cytometry was applied to measure phagocytosis of PBMCs. Cytokine mRNA and protein expression levels of LPS-stimulated PBMCs with or without CST were measured by qRT-PCR and ELISA. The transcriptomic profile of CST-treated PBMCs was investigated by RNA-sequencing. Gene Ontology (GO) and Kyoto Encylopedia of Genes and Genomes (KEGG) were applied to find potential signalling pathways. PBMCs showed a significant increase in phagocytic activity at 6 h after being incubated with CST at the concentration of 10 µg/mL. In the presence of LPS, CST maintained and promoted the expression of TNF-α and chemokine CCL24. The content of pro-inflammatory cytokines, such as IL-1ß, IL-6 and IFN-γ, which were released from LPS-stimulated PBMCs, was reduced by CST at 6 h. Anti-inflammatory cytokines, such as IL-4, IL-13 and TGF-ß1, were significantly increased by CST at 24 h. A total of 277 differentially expressed immune-related genes (DEIRGs) were detected and cytokine-cytokine receptor interaction was highly enriched. CST presented obvious anti-inflammatory and immunoregulatory effects in LPS-induced PBMCs inflammatory model not only by improving the ability of PBMCs to clear pathogens but also by decreasing pro-inflammatory cytokines and increasing anti-inflammatory cytokines. And the mechanism may be related to cytokine-cytokine receptor interaction.