Expertise increases planning depth in human gameplay.

A hallmark of human intelligence is the ability to plan multiple steps into the future1,2. Despite decades of research3-5, it is still debated whether skilled decision-makers plan more steps ahead than novices6-8. Traditionally, the study of expertise in planning has used board games such as chess, but the complexity of these games poses a barrier to quantitative estimates of planning depth. Conversely, common planning tasks in cognitive science often have a lower complexity9,10 and impose a ceiling for the depth to which any player can plan. Here we investigate expertise in a complex board game that offers ample opportunity for skilled players to plan deeply. We use model fitting methods to show that human behaviour can be captured using a computational cognitive model based on heuristic search. To validate this model, we predict human choices, response times and eye movements. We also perform a Turing test and a reconstruction experiment. Using the model, we find robust evidence for increased planning depth with expertise in both laboratory and large-scale mobile data. Experts memorize and reconstruct board features more accurately. Using complex tasks combined with precise behavioural modelling might expand our understanding of human planning and help to bridge the gap with progress in artificial intelligence.

Imbalanced and Unchecked: The Role of Metal Dyshomeostasis in Driving COPD Progression.

Chronic obstructive pulmonary disease (COPD) is a chronic respiratory condition characterized by persistent inflammation and oxidative stress, which ultimately leads to progressive restriction of airflow. Extensive research findings have cogently suggested that the dysregulation of essential transition metal ions, notably iron, copper, and zinc, stands as a critical nexus in the perpetuation of inflammatory processes and oxidative damage within the lungs of COPD patients. Unraveling the intricate interplay between metal homeostasis, oxidative stress, and inflammatory signaling is of paramount importance in unraveling the intricacies of COPD pathogenesis. This comprehensive review aims to examine the current literature on the sources, regulation, and mechanisms by which metal dyshomeostasis contributes to COPD progression. We specifically focus on iron, copper, and zinc, given their well-characterized roles in orchestrating cytokine production, immune cell function, antioxidant depletion, and matrix remodeling. Despite the limited number of clinical trials investigating metal modulation in COPD, the advent of emerging methodologies tailored to monitor metal fluxes and gauge responses to chelation and supplementation hold great promise in unlocking the potential of metal-based interventions. We conclude that targeted restoration of metal homeostasis represents a promising frontier for ameliorating pathological processes driving COPD progression.

Upregulation of PTPRC and Interferon Response Pathways in HIV-1 Seroconverters Prior to Infection.

Human immunodeficiency virus 1 (HIV-1) exposed seronegative (HESN) individuals may have unique characteristics that alter susceptibility to HIV-1 infection. However, identifying truly exposed HESN is challenging. We utilized stored data and biospecimens from HIV-1 serodifferent couple cohorts, in which couples' HIV-1 exposures were quantified based on unprotected sex frequency and viral load of the partner with HIV-1. We compared peripheral blood gene expression between 15 HESN and 18 seroconverters prior to infection. We found PTPRC (encoding CD45 antigen) and interferon-response pathways had significantly higher expression among individuals who went on to become seropositive and thus may be a signature for increased acquisition risk.

[Optimization of prediction model for personalized water pills based on semantic analysis of traditional Chinese medicine materials].

This study aims to optimize the prediction model of personalized water pills that has been established by our research group. Dioscoreae Rhizoma, Leonuri Herba, Codonopsis Radix, Armeniacae Semen Amarum, and calcined Oyster were selected as model medicines of powdery, fibrous, sugary, oily, and brittle materials, respectively. The model prescriptions were obtained by uniform mixing design. With hydroxypropyl methylcellulose E5(HPMC-E5) aqueous solution as the adhesive, personalized water pills were prepared by extrusion and spheronizaition. The evaluation indexes in the pill preparation process and the multi-model statistical analysis were employed to optimize and evaluate the prediction model of personalized water pills. The prediction equation of the adhesive concentration was obtained as follows: Y_1=-4.172+3.63X_A+15.057X_B+1.838X_C-0.997X_D(adhesive concentration of 10% when Y_1<0, and 20% when Y_1>0). The overall accuracy of the prediction model for adhesive concentration was 96.0%. The prediction equation of adhesive dosage was Y_2=6.051+94.944X_A~(1.5)+161.977X_B+70.078X_C~2+12.016X_D~(0.3)+27.493X_E~(0.3)-2.168X_F~(-1)(R~2=0.954, P<0.001). Furthermore, the semantic prediction model for material classification of traditional Chinese medicines was used to classify the materials contained in the prescription, and thus the prediction model of personalized water pills was evaluated. The results showed that the prescriptions for model evaluation can be prepared with one-time molding, and the forming quality was better than that established by the research group earlier. This study has achieved the optimization of the prediction model of personalized water pills.

[Intelligent material classification of traditional Chinese medicine based on semantic analysis].

A method for material classification of traditional Chinese medicines based on the physical properties of powder has been established by our research group. This method involves pre-treatment of traditional Chinese medicine decoction pieces, powder preparation, and determination of physical properties, being cumbersome. In this study, the word segmentation logic of semantic analysis was adopted to establish the thesaurus and local standardized semantic word segmentation database with the macroscopic and microscopic characteristics of 36 model traditional Chinese medicines as the basic data. The physical properties of these medicines have been determined and the classification of these medicines is clear in the cluster analysis. A total of 55 keywords for powdery, fibrous, sugary, oily, and brittle materials were screened by association rules and the set inclusion and exclusion criteria, and the weights of the keywords were calculated. Furthermore, the algorithms of the keyword matching scores and the computation rules of the single or multiple material classification were established for building the intelligent model of semantic analysis for the material classification. The semantic classification results of the other 35 TCMs except Pseudostellariae Radix(multi-material medicine) agreed with the clustering results based on the physical properties of the powder, with an agreement rate of 97.22%. In model validation, the prediction results of semantic classification of traditional Chinese medicines were consistent with the clustering results based on the physical properties of powder, with an agreement rate of 83.33%. The results showed that the method of material classification based on semantic analysis was feasible, which laid a foundation for the development of intelligent decision-making technology for personalized traditional Chinese medicine preparations.

Multifunctional Cellulose Nanocrystals Electrolyte Additive Enable Ultrahigh-Rate and Dendrite-Free Zn Anodes for Rechargeable Aqueous Zinc Batteries.

The design of aqueous zinc (Zn) chemistry energy storage with high rate-capability and long serving life is a great challenge due to its inhospitable coordination environment and dismal interfacial chemistry. To bridge this big gap, herein, we build a highly reversible aqueous Zn battery by taking advantages of the biomass-derived cellulose nanocrystals (CNCs) electrolyte additive with unique physical and chemical characteristics simultaneously. The CNCs additive not only serves as fast ion carriers for enhancing Zn2+ transport kinetics but regulates the coordination environment and interface chemistry to form dynamic and self-repairing protective interphase, resulting in building ultra-stable Zn anodes under extreme conditions. As a result, the engineered electrolyte system achieves a superior average coulombic efficiency of 97.27 % under 140 mA cm-2, and steady charge-discharge for 982 h under 50 mA cm-2, 50 mAh cm-2, which proposes a universal pathway to challenge aqueous Zn chemistry in green, sustainable, and large-scale applications.

Mettl14 mediates the inflammatory response of macrophages in atherosclerosis through the NF-κB/IL-6 signaling pathway.

The inflammatory response of macrophages has been reported to play a critical role in atherosclerosis. The inflammatory state of macrophages is modified by epigenetic reprogramming. m6A RNA methylation is an epigenetic modification of RNAs. However, little is known about the potential roles and underlying mechanisms of m6A modification in macrophage inflammation. Herein, we showed that the expression of the m6A modification "writer" Mettl14 was increased in coronary heart disease and LPS-stimulated THP-1 cells. Knockdown of Mettl14 promoted M2 polarization of macrophages, inhibited foam cell formation and decreased migration. Mechanistically, the expression of Myd88 and IL-6 was decreased in Mettl14 knockdown cells. Through m6A modification, Mettl14 regulated the stability of Myd88 mRNA. Furthermore, Myd88 affected the transcription of IL-6 via the distribution of p65 in nuclei rather than directly regulating the expression of IL-6 through m6A modification. In vivo, Mettl14 gene knockout significantly reduced the inflammatory response of macrophages and the development of atherosclerotic plaques. Taken together, our data demonstrate that Mettl14 plays a vital role in macrophage inflammation in atherosclerosis via the NF-κB/IL-6 signaling pathway, suggesting that Mettl14 may be a promising therapeutic target for the clinical treatment of atherosclerosis.

[Classification optimization of traditional Chinese medicine materials based on additive physical properties of powder].

According to the method of predicting the physical properties of oily powder based on the additive physical properties of Chinese medicinal powder, Dioscoreae Rhizoma and calcined Ostreae Concha with high sieve rate and good fluidity were mixed and crushed with Persicae Semen, Platycladi Semen, Raphani Semen, Ziziphi Spinosae Semen, and other typical oily materials with high fatty oil content in proportion to obtain 23 mixed powders. Fifteen physical properties such as bulk density, water absorption, and maximum torque force were measured, and the physical properties of typical oily powders were predicted. When the mixing and grinding ratio was in the range of 5∶1-1∶1, the r value in the correlation equation between the weighted average score of the mixed powder and the powder proportion ranged from 0.801 to 0.986, and the linearity was good, indicating that the method of predicting the physical properties of oily powder based on the additive physical properties of traditional Chinese medicine(TCM)powder was feasible. The results of cluster analysis showed that the classification boundaries of the five kinds of TCM materials were clear, and the similarity of the physical fingerprints of powdery and oily materials decreased from 80.6% to 37.2%, which solved the problem of fuzzy classification boundaries of powdery and oily materials due to the lack of representativeness of oily material model drugs. The classification of TCM materials was optimized, laying a foundation for optimizing the prediction model of the prescription of personalized water-paste pills.

Light intensity alters the effects of light-induced circadian disruption on glucose and lipid metabolism in mice.

Circadian disruption induced by rotating light cycles has been linked to metabolic disorders. However, how the interaction of light intensity and light cycle affects metabolism under different diets remains to be explored. Eighty mice were first randomly stratified into the low-fat diet (LFD, n = 40) or high-fat diet (HFD, n = 40) groups. Each group was further randomly subdivided into four groups (n = 8-12 per group) in terms of different light intensities [lower (LI, 78 lx) or higher intensity (HI, 169 lx)] and light cycles [12-h light:12-h dark cycle or circadian-disrupting (CD) light cycle consisting of repeated 6-h light phase advancement]. Body weight was measured weekly. At the end of the 16-wk experiment, mice were euthanized for serum and pathological analysis. Glucose and insulin tolerance tests were performed during the last 2 wk. The CD cycle increased body weight gain, adipocyte area, glucose intolerance, and insulin resistance of LFD as well as HFD mice under HI but not LI condition. Moreover, the serum and hepatic triglyceride levels increased with LFD-HI treatment, regardless of light cycle. In addition, the CD cycle improved lipid and glucose metabolism under HFD-LI condition. In summary, the detrimental effects of the CD cycle on metabolism were alleviated under LI condition, especially in HFD mice. These results indicate that modulating light intensity is a potential strategy to prevent the negative metabolic consequences associated with jet lag or shift work.NEW & NOTEWORTHY Glucose and lipid homeostasis is altered by the CD cycles in a light-intensity-dependent manner. Lower-intensity light reverses the negative metabolic effects of the CD cycles, especially under HFD feeding. The interaction of light intensity and light cycle on metabolism is independent of energy intake and eating pattern. Glucose metabolic disorders caused by rotating light cycles occur along with compensatory ß-cell mass expansion.

Decreased DNA Methylation of RGMA is Associated with Intracranial Hypertension After Severe Traumatic Brain Injury: An Exploratory Epigenome-Wide Association Study.

BACKGROUND: Cerebral edema and intracranial hypertension are major contributors to unfavorable prognosis in traumatic brain injury (TBI). Local epigenetic changes, particularly in DNA methylation, may influence gene expression and thus host response/secondary injury after TBI. It remains unknown whether DNA methylation in the central nervous system is associated with cerebral edema severity or intracranial hypertension post TBI. We sought to identify epigenome-wide DNA methylation patterns associated with these forms of secondary injury after TBI. METHODS: We obtained genome-wide DNA methylation profiles of DNA extracted from ventricular cerebrospinal fluid samples at three different postinjury time points from a prospective cohort of patients with severe TBI (n = 89 patients, 254 samples). Cerebral edema and intracranial pressure (ICP) measures were clustered to generate composite end points of cerebral edema and ICP severity. We performed an unbiased epigenome-wide association study (EWAS) to test associations between DNA methylation at 419,895 cytosine-phosphate-guanine (CpG) sites and cerebral edema/ICP severity categories. Given inflated p values, we conducted permutation tests for top CpG sites to filter out potential false discoveries. RESULTS: Our data-driven hierarchical clustering across six cerebral edema and ICP measures identified two groups differing significantly in ICP based on the EWAS-identified CpG site cg22111818 in RGMA (Repulsive guidance molecule A, permutation p = 4.20 × 10-8). At 3-4 days post TBI, patients with severe intracranial hypertension had significantly lower levels of methylation at cg22111818. CONCLUSIONS: We report a novel potential relationship between intracranial hypertension after TBI and an acute, nonsustained reduction in DNA methylation at cg22111818 in the RGMA gene. To our knowledge, this is the largest EWAS in severe TBI. Our findings are further strengthened by previous findings that RGMA modulates axonal repair in other central nervous system disorders, but a role in intracranial hypertension or TBI has not been previously identified. Additional work is warranted to validate and extend these findings, including assessment of its possible role in risk stratification, identification of novel druggable targets, and ultimately our ability to personalize therapy in TBI.

Satellite Network Task Deployment Method Based on SDN and ICN.

With the rapid development of 5G and the Internet of Things, satellite networks are emerging as an indispensable part of realizing wide-area coverage. The growth of the constellation of low-orbit satellites makes it possible to deploy edge computing services in satellite networks. This is, however, challenging due to the topological dynamics and limited resources of satellite networks. To improve the performance of edge computing in a satellite network, we propose a satellite network task deployment method based on SDN (software-defined network) and ICN (information-centric network). In this method, based on the full analysis of satellite network resources, a mission deployment model of a low-orbit satellite network is established. The genetic algorithm is then used to solve the proposed method. Experiments confirm that this method can effectively reduce the response delay of the tasks and the network traffic caused by task processing.

Facile, Electrochemical Chlorination of Graphene from an Aqueous NaCl Solution.

We report a facile approach to directly chlorinate graphene from an aqueous sodium chloride solution under ambient conditions. By applying a moderate anodic voltage to substrate-supported monolayer graphene, the resultant chlorine radicals generated at the graphene surface enable efficient chlorination: X-ray photoelectron spectrum confirms the formation of C-Cl bonds, and reaction voltage-tunable Cl:C atomic ratios of up to 17% are achieved. In comparison, we find the corresponding electrochemical graphene bromination and iodination reactions much less viable. Electrical and Raman characterizations show substantial p-doping for the chlorinated graphene, yet good basal-plane integrity and electrical properties are maintained. Interference reflection microscopy and pH-dependent experiments next help elucidate the competition between the radical-mediated electrochemical chlorination and oxidation in the process, and rationalize acidic conditions for optimal chlorination. Reaction in a mixed NaCl-NaN3 solution shows the electrochemical chlorination to be fully suppressed by azidation, yet a sequential, two-step chlorination-azidation approach permits facile bifunctionalization.

Lesion Segmentation in Gastroscopic Images Using Generative Adversarial Networks.

The segmentation of the lesion region in gastroscopic images is highly important for the detection and treatment of early gastric cancer. This paper proposes a novel approach for gastric lesion segmentation by using generative adversarial training. First, a segmentation network is designed to generate accurate segmentation masks for gastric lesions. The proposed segmentation network adds residual blocks to the encoding and decoding path of U-Net. The cascaded dilated convolution is also added at the bottleneck of U-Net. The residual connection promotes information propagation, while dilated convolution integrates multi-scale context information. Meanwhile, a discriminator is used to distinguish the generated and real segmentation masks. The proposed discriminator is a Markov discriminator (Patch-GAN), which discriminates each [Formula: see text] matrix in the image. In the process of network training, the adversary training mechanism is used to iteratively optimize the generator and the discriminator until they converge at the same time. The experimental results show that the dice, accuracy, and recall are 86.6%, 91.9%, and 87.3%, respectively. These metrics are significantly better than the existing models, which proves the effectiveness of this method and can meet the needs of clinical diagnosis and treatment.

Azidated Graphene: Direct Azidation from Monolayers, Click Chemistry, and Bulk Production from Graphite.

The inertness of the graphene basal plane has notably limited its viable chemical modification pathways. We report direct azidation and subsequent click chemistry of the graphene basal plane through the electrochemical oxidation of an aqueous sodium azide solution at the graphene surface. An ∼20% nitrogen-to-carbon ratio is achieved for monolayer graphene under ambient conditions and neutral pH, and the degree of functionalization is tunable through the applied voltage. The functionalized azide groups enable both copper-catalyzed and copper-free alkyne cycloaddition click chemistry, as well as subsequent bioconjugation, and fluorescence microscopy indicates uniform functionalization across the graphene surface. Notably, we find that as the azidation, cycloaddition, and bioconjugation processes substantially shift the graphene doping level, high electrical conductivity and carrier mobility are maintained throughout the different functionalization states. By integrating the electrochemical azidation scheme with electrochemical exfoliation, we further demonstrate one-step bulk production of azidated graphene flakes from graphite. We thus open a new door to the facile preparation of diverse graphene derivatives under ambient conditions.

Efficient Suppression of Chain Transfer and Branching via Cs -Type Shielding in a Neutral Nickel(II) Catalyst.

An effective shielding of both apical positions of a neutral NiII active site is achieved by dibenzosuberyl groups, both attached via the same donors' N-aryl group in a Cs -type arrangement. The key aniline building block is accessible in a single step from commercially available dibenzosuberol. This shielding approach suppresses chain transfer and branch formation to such an extent that ultrahigh molecular weight polyethylenes (5×106  g mol-1 ) are accessible, with a strictly linear microstructure (<0.1 branches/1000C). Key features of this highly active (4.3×105  turnovers h-1 ) catalyst are an exceptionally facile preparation, thermal robustness (up to 90 °C polymerization temperature), ability for living polymerization and compatibility with THF as a polar reaction medium.

Structure and phase behavior of poly(acrylic acid)-ferric ion complex aqueous solutions.

In this study, we investigate the conformational evolution and phase behavior of poly(acrylic acid) (PAA) solution upon the introduction of ferric ions through a combination of small angle X-ray scattering (SAXS), turbidity, zeta-potential and pH measurements. Salt-free PAA aqueous solution is a weak polyelectrolyte solution. The introduced ferric ion can coordinate with the carboxylic acid groups, yielding H+ ions to lower the pH value. We find two transitions with increasing concentration of the ferric ions: a polyelectrolyte to apparent good solution transition characterized by the disappearance of the polyelectrolyte peak in the X-ray scattering, and a phase separation characterized by a sharp increase of the turbidity. Detailed analyses of pH and zeta-potential reveal the molecular details of the three regions. Namely, (1) the polyelectrolyte region locates at log[H+] (= -pH) ≫ log(3[Fe3+]), where the H+ ions are mainly contributed from the dissociation of carboxylic acid, and the polymer chains are negatively charged, (2) the good solution region locates at log[H+] ∼ log(3[Fe3+]), where the H+ ions are mainly yielded from coordination between COO- and Fe3+, and polymer chains are nearly neutralized, and (3) the phase separation locates at log[H+] ≪ log(3[Fe3+]), where the Fe3+ ions are not fully coordinated, and charge inversion occurs. The phase separation occurs when the chains are densely and tightly coordinated with Fe3+ ions.

Effects of prepartum zinc-methionine supplementation on feed digestibility, rumen fermentation patterns, immunity status, and passive transfer of immunity in dairy cows.

The aim of this study was to determine the effects of prepartum supplementation of zinc-methionine (Zn-Met) on feed digestibility, rumen fermentation patterns, and immunity status in dams and passive immunity transfer in their calves. A randomized complete design was used in this study. Forty multiparous Holstein dairy cows in late pregnancy (60 d before the expected calving date) were blocked by parity (2.1 ± 0.3), body weight (651 ± 52 kg), and expected calving date, and randomly assigned to 1 of 4 treatments. Cows were supplemented with Zn as Zn-Met at 0, 20, 40, or 60 mg/kg of dry matter (DM) from 60 d before expected calving date to the calving day. Though the nutrient digestibility was not affected by Zn supplementation, DM intake, Zn digestibility, and Zn deposition increased linearly with increasing Zn-Met supplementation. Ruminal pH and molar proportion of individual volatile fatty acids were similar, whereas a linear decrease and increase were observed in ruminal ammonia and microbial crude protein concentration, respectively, with increasing Zn-Met supplementation. Maternal serum concentration of alkaline phosphatase, carboxypeptidase, Cu and Zn superoxide dismutase, and total antioxidant capacity were greater in cows supplemented with >40 mg of Zn/kg of DM compared with the control group. With increasing Zn-Met supplementation, maternal blood concentration of IL-1 decreased linearly, whereas IL-2 and IL-6 increased linearly, and no differences were observed in IL-4. Concentration of nonesterified fatty acids and ß-hydroxybutyric acids in maternal blood was similar between treatments. No difference was observed in colostrum composition with increasing Zn-Met supplementation. Concentration of Zn and immunoglobulins (including IgA, IgG, and IgM) in maternal blood did not differ among treatments. However, Zn concentration in colostrum and blood of calves increased linearly. The concentration of IgA and IgM in colostrum increased linearly with increasing Zn-Met supplementation, whereas no differences in immunoglobulins were observed in calf blood. In conclusion, Zn supplementation as Zn-Met at 40 of mg/kg of DM may improve antioxidant activity of dam and potentially increase passive immunity transfer in calves.

Ordered-Assembly Conductive Nanowires Array with Tunable Polymeric Structure for Specific Organic Vapor Detection.

An artificial organic vapor sensor based on a finite number of 1D nanowires arrays can provide a strategy to allow classification and identification of different analytes with high efficiency, but fabricating a 1D nanowires array is challenging. Here, a coaxial Ag/polymer nanowires array is prepared as an organic vapor sensor with specific recognition, using a strategy combining superwettability-based nanofabrication and polymeric swelling-induced resistance change. Such organic vapor sensor containing commercial polymers can successfully classify and identify various organic vapors with good separation efficiency. An Ag/polymer nanowires array with synthetic polyethersulfone polymers is also fabricated, through molecular structure modification of the polymers, to distinguish the similar organic vapors of methanol and ethanol. Theoretical simulation results demonstrate introduction of specific molecular interaction between the designed polymers and organic vapors can improve the specific recognition performance of the sensors.

Understanding conformational and dynamical evolution of semiflexible polymers in shear flow.

A clear description of the conformational and dynamical evolution of polymer chains in shear flow is the fundamental basis of microfluidic separations and macroscopic rheological behaviors. We employ graph theory analysis to analyze the local deformation and dynamics of linear polymer chains with different rigidities in shear flow based on the simulation trajectories that record the instantaneous conformations and dynamics. Our results show that all semiflexible chains experience quasi-periodic tumbling motions when the shear strain overwhelms the U-shape (or S-shape) deformation energy barrier. More interestingly, the contact map provides solid evidence for the asymmetric deformation in the whole tumbling motion. In the stretching process: at small and intermediate shear strength, flexible polymers show a quasi-affine deformation while semiflexible ones are initially unfolded from the center of the chains, then both of them follow the extension with half dumbbell- or dumbbell-like ends; at high shear strength, all polymer chains present only a dumbbell-like extension. In the collapse process, all chains prefer to initiate the folding from chain ends. This finding can facilitate our understanding on how semiflexible polymer chains relax and dissipate the stress in shear flow.

The Effects of Photobiomodulation on MC3T3-E1 Cells via 630 nm and 810 nm Light-Emitting Diode.

BACKGROUND Photobiomodulation (PBM) has been explored as a promising therapeutic strategy to regulate bone cell growth; however, the effects of PBM on osteoblast cell lines remains poorly understood. In addition, as a light source of PBM, the light uniformity of light-emitting diode (LED) devices has not been given enough attention. MATERIAL AND METHODS Here, we sought to investigate the effects of PBM on MC3T3-E1 cells via 630 nm and 810 nm light from a newly designed LED with high uniformity of light. Cell proliferation, flow cytometric analysis, alkaline phosphatase (ALP) staining, ALP activity, Alizarin Red S staining, and quantitative real-time polymerase chain reaction (qRT-PCR) were carried out to assess treatment response. MC3T3-E1 cells were irradiated with LED devices (630±5 nm and 810±10 nm, continuous wave) for 200 seconds at a power density of 5 mW/cm² once daily. RESULTS Increases in cell proliferation and decreases in cell apoptosis were evident following irradiation. ALP staining intensity and activity were also significantly increased following irradiation. Level of mineralization was obviously enhanced in irradiated groups compared with non-irradiated controls. qRT-PCR also showed significant increases in mRNA expression of osteocalcin (OCN) and osteoprotegerin (OPG) in the irradiated groups. CONCLUSIONS Our results showed that LED PBM could promote the proliferation, ALP staining intensity and activity, level of mineralization, gene expression of OCN and OPG of MC3T3-E1 cells, with no significant difference between the 630 nm- and 810 nm-irradiated groups.