A new artificial intelligence system for both stomach and small bowel capsule endoscopy.

BACKGROUND AND AIMS: Despite the benefits of artificial intelligence (AI) in small bowel (SB) capsule endoscopy (CE) image reading, information on its application in the stomach and SB CE is lacking. METHODS: In this multicenter, retrospective diagnostic study, gastric imaging data were added to the deep learning (DL)-based SmartScan (SS), which has been described previously. A total of 1,069 magnetically controlled gastrointestinal (GI) CE examinations (comprising 2,672,542 gastric images) were used in the training phase for recognizing gastric pathologies, producing a new AI algorithm named SS Plus. 342 fully automated, magnetically controlled CE (FAMCE) examinations were included in the validation phase. The performance of both senior and junior endoscopists with both the SS Plus-Assisted Reading (SSP-AR) and conventional reading (CR) modes was assessed. RESULTS: SS Plus was designed to recognize 5 types of gastric lesions and 17 types of SB lesions. SS Plus reduced the number of CE images required for review to 873.90 (1000) (median, IQR 814.50-1,000) versus 44,322.73 (42,393) (median, IQR 31,722.75-54,971.25) for CR. Furthermore, with SSP-AR, endoscopists took 9.54 min (8.51) (median, IQR 6.05-13.13) to complete the CE video reading. In the 342 CE videos, SS Plus identified 411 gastric and 422 SB lesions, whereas 400 gastric and 368 intestinal lesions were detected with CR. Moreover, junior endoscopists remarkably improved their CE image reading ability with SSP-AR. CONCLUSIONS: Our study shows that the newly upgraded DL-based algorithm SS Plus can detect GI lesions and help improve the diagnostic performance of junior endoscopists in interpreting CE videos.

Intermediate open state of CD4-bound HIV-1 env heterotrimers in asia CRFs.

The HIV-1 envelope glycoprotein (Env) plays crucial role in viral infection by facilitating viral attachment to host cells and inducing fusion of the virus with the host cell membrane. This fusion allows the HIV-1 viral genome to enter the target cell then triggering various stages of the viral life cycle. The native Env directly interacts with the main receptor CD4 and the co-receptor (CCR5 or CXCR4) in human cell membrane then induces membrane fusion. The elucidation of the structure of Env with CD4 and co-receptors in different HIV-1 subtypes is essential for the understanding of the mechanism of virus entry. Here we report the Cryo-EM structure of the CD4-bound HIV-1 heterotrimeric Env from Asia prevalent CRF07_BC CH119 strain. In this structure, the binding of three CD4 molecules with Env induced extensively conformational changes in gp120, resulting in the transformation of the Env from close state to intermediate open state. Additionally, the conformational shift of V1/V2 loops of the heterotrimeric Env allosterically expose the V3 loop and promoting the further interactions with co-receptor CCR5 or CXCR4. These findings not only illustrate the structural complexity and plasticity of HIV-1 Env but also give new insights how the biological trimeric Env initialize the immune recognition and membrane fusion.

Water Transport-Induced Liquid-Liquid Phase Separation Facilitates Gelation for Controllable and Facile Fabrication of Physically Crosslinked Microgels.

Physically crosslinked microgels (PCMs) offer a biocompatible platform for various biomedical applications. However, current PCM fabrication methods suffer from their complexity and poor controllability, due to their reliance on altering physical conditions to initiate gelation and their dependence on specific materials. To address this issue, a novel PCM fabrication method was devised, which employs water transport-induced liquid-liquid phase separation (LLPS) to trigger the intermolecular interaction-supported sol-gel transition within aqueous emulsion droplets. This method enables the controllable and facile generation of PCMs through a single emulsification step, allowing for the facile production of PCMs with various materials and sizes, as well as controllable structures and mechanical properties. Moreover, this PCM fabrication method holds great promise for diverse biomedical applications. The interior of the PCM not only supports the encapsulation and proliferation of bacteria but also facilitates the encapsulation of eukaryotic cells after transforming the system into an all-aqueous emulsion. Furthermore, through appropriate surface functionalization, the PCMs effectively activate T cells in vitro upon co-culturing. This work represents an advancement in PCM fabrication and offers new insights and perspectives for microgel engineering. This article is protected by copyright. All rights reserved.

Does digital infrastructure construction impact urban carbon emission reduction? Evidence from China's smart city construction.

As the cornerstone of the digital economy, the construction of digital infrastructure plays a crucial role in promoting China's high-quality economic growth.. Against the backdrop of the "dual-carbon" goals, the development of digital infrastructure will provide new momentum for carbon emissions reduction in urban areas. This study utilizes unbalanced panel data from 277 prefecture-level cities in China between 2008 and 2019, treating the smart city construction as a quasi-natural experiment, to systematically evaluate the impact of the pilot construction of smart city on urban carbon emissions intensity. The research findings reveal that the construction of the smart city has significantly contributed to the reduction of urban carbon emissions intensity, indicating that digital infrastructure contributes to urban carbon emission reduction. The reduction of carbon emissions resulting from smart city construction is particularly significant in the East and Central regions., as well as regions with high financial development levels, regions with high human capital levels and non resource-based cities. The construction of the smart city primarily achieves the reduction of urban carbon emissions intensity through two main pathways: improving the penetration rate of digital infrastructure and enhancing technological innovation capability. Therefore, this study recommends that local governments strengthen the integration and penetration of digital infrastructure with traditional industries, foster urban innovation vitality, and accelerate the transformation towards green and low-carbon cities.

Indian Ocean temperature anomalies predict long-term global dengue trends.

Despite identifying El Niño events as a factor in dengue dynamics, predicting the oscillation of global dengue epidemics remains challenging. Here, we investigate climate indicators and worldwide dengue incidence from 1990 to 2019 using climate-driven mechanistic models. We identify a distinct indicator, the Indian Ocean basin-wide (IOBW) index, as representing the regional average of sea surface temperature anomalies in the tropical Indian Ocean. IOBW is closely associated with dengue epidemics for both the Northern and Southern hemispheres. The ability of IOBW to predict dengue incidence likely arises as a result of its effect on local temperature anomalies through teleconnections. These findings indicate that the IOBW index can potentially enhance the lead time for dengue forecasts, leading to better-planned and more impactful outbreak responses.

Discovery of an immunosuppressive functional metabolite from the insect-derived endophytic Aspergillus taichungensis SMU01.

Three p-terphenyl metabolites (1-3), three indole-diterpenoids (4-6), an herbicide sesquiterpene (7), a flavonoid (8), and five other small molecules containing nitrogen (9-13) were isolated from the medicinal insect (Periplaneta americana)-derived endophytic Aspergillus taichungensis SMU01. Their chemical structures were elucidated on the basis of spectroscopic data and quantum chemical computational methods. Biological activity of these isolates in the differentiation of mouse CD4+ T cell subsets was evaluated. Importantly, metabolites 2 targeting JAK-STAT signaling pathway could hold potential benefits in maintaining peripheral immune homeostasis and alleviating the progression of autoimmune diseases.

Glutathione-responsive Aggregation-induced Emission Photosensitizers for Enhanced Photodynamic Therapy of Lung Cancer.

Lung cancer, a highly prevalent and lethal form of cancer, is often associated with oxidative stress. Photodynamic therapy (PDT) has emerged as a promising alternative therapeutic tool in cancer treatments, but its efficacy is closely correlated to the photosensitizers generating reactive oxygen species (ROS) and the antioxidant capacity of tumor cells. In particular, glutathione (GSH) can reduce the ROS and thus compromise PDT efficacy. In this study, a GSH-responsive near-infrared photosensitizer (TBPPN) based on aggregation-induced emission for real-time monitoring of GSH levels and enhanced PDT for lung cancer treatment is developed. The strategic design of TBPPN, consisting of a donor-acceptor structure and incorporation of dinitrobenzene, enables dual functionality by not only the fluorescence being activated by GSH but also depleting GSH to enhance the cytotoxic effect of PDT. TBPPN demonstrates synergistic PDT efficacy in vitro against A549 lung cancer cells by specifically targeting different cellular compartments and depleting intracellular GSH. In vivo studies further confirm that TBPPN can effectively inhibit tumor growth in a mouse model with lung cancer, highlighting its potential as an integrated agent for the diagnosis and treatment of lung cancer. This approach enhances the effectiveness of PDT for lung cancer and deserves further exploration of its potential for clinical application.

Analysis of MRI features and associated factors of the pituitary neuroendocrine tumor streaky sign.

OBJECTIVES: Observation of pituitary neuroendocrine tumors with streaky sign on MRI, analysis of their features on imaging and further investigation of the relationship between the direction of the streak sign and the direction of optimal tumor expansion. METHODS: The MR images of 237 patients with pituitary neuroendocrine tumors were retrospectively analyzed. The streaky-like high signal with a substantial length of more than 10 mm and obvious enhancement on T1WI was defined as the streaky sign. Finally, 66 patients were included in the study, comprising 33 patients with streaky sign pituitary neuroendocrine tumors and 33 randomly selected patients with non-streaky sign pituitary neuroendocrine tumors. The general condition of these 66 patients, the imaging features of the tumor, and the measurement and analysis of the direction of the streaky sign in relation to the direction of optimal tumor extension were observed and analyzed. RESULTS: On MRI, 85 streaky signs were observed. The average deviation between the direction angle of all the streaky signs and the optimal extension direction angle of the tumor was approximately 11°. The longest streaky sign angle was positively correlated with the optimal extension angle of the tumor, with a correlation coefficient of 0.967. CONCLUSION: The presence of a streaky sign of pituitary neuroendocrine tumors may indicate a dilated sinus or a small blood vessel. Its direction is highly consistent with the optimal extension direction of the tumor, which has a certain supporting effect on the long-distance growth of the tumor.

De novo variants in the non-coding spliceosomal snRNA gene RNU4-2 are a frequent cause of syndromic neurodevelopmental disorders.

Around 60% of individuals with neurodevelopmental disorders (NDD) remain undiagnosed after comprehensive genetic testing, primarily of protein-coding genes1. Increasingly, large genome-sequenced cohorts are improving our ability to discover new diagnoses in the non-coding genome. Here, we identify the non-coding RNA RNU4-2 as a novel syndromic NDD gene. RNU4-2 encodes the U4 small nuclear RNA (snRNA), which is a critical component of the U4/U6.U5 tri-snRNP complex of the major spliceosome2. We identify an 18 bp region of RNU4-2 mapping to two structural elements in the U4/U6 snRNA duplex (the T-loop and Stem III) that is severely depleted of variation in the general population, but in which we identify heterozygous variants in 119 individuals with NDD. The vast majority of individuals (77.3%) have the same highly recurrent single base-pair insertion (n.64_65insT). We estimate that variants in this region explain 0.41% of individuals with NDD. We demonstrate that RNU4-2 is highly expressed in the developing human brain, in contrast to its contiguous counterpart RNU4-1 and other U4 homologs, supporting RNU4-2's role as the primary U4 transcript in the brain. Overall, this work underscores the importance of non-coding genes in rare disorders. It will provide a diagnosis to thousands of individuals with NDD worldwide and pave the way for the development of effective treatments for these individuals.

Improved dual-aggregation polyp segmentation network combining a pyramid vision transformer with a fully convolutional network.

Automatic and precise polyp segmentation in colonoscopy images is highly valuable for diagnosis at an early stage and surgery of colorectal cancer. Nevertheless, it still posed a major challenge due to variations in the size and intricate morphological characteristics of polyps coupled with the indistinct demarcation between polyps and mucosas. To alleviate these challenges, we proposed an improved dual-aggregation polyp segmentation network, dubbed Dua-PSNet, for automatic and accurate full-size polyp prediction by combining both the transformer branch and a fully convolutional network (FCN) branch in a parallel style. Concretely, in the transformer branch, we adopted the B3 variant of pyramid vision transformer v2 (PVTv2-B3) as an image encoder for capturing multi-scale global features and modeling long-distant interdependencies between them whilst designing an innovative multi-stage feature aggregation decoder (MFAD) to highlight critical local feature details and effectively integrate them into global features. In the decoder, the adaptive feature aggregation (AFA) block was constructed for fusing high-level feature representations of different scales generated by the PVTv2-B3 encoder in a stepwise adaptive manner for refining global semantic information, while the ResidualBlock module was devised to mine detailed boundary cues disguised in low-level features. With the assistance of the selective global-to-local fusion head (SGLFH) module, the resulting boundary details were aggregated selectively with these global semantic features, strengthening these hierarchical features to cope with scale variations of polyps. The FCN branch embedded in the designed ResidualBlock module was used to encourage extraction of highly merged fine features to match the outputs of the Transformer branch into full-size segmentation maps. In this way, both branches were reciprocally influenced and complemented to enhance the discrimination capability of polyp features and enable a more accurate prediction of a full-size segmentation map. Extensive experiments on five challenging polyp segmentation benchmarks demonstrated that the proposed Dua-PSNet owned powerful learning and generalization ability and advanced the state-of-the-art segmentation performance among existing cutting-edge methods. These excellent results showed our Dua-PSNet had great potential to be a promising solution for practical polyp segmentation tasks in which wide variations of data typically occurred.

Satellite NO2 Retrieval Complicated by Aerosol Composition over Global Urban Agglomerations: Seasonal Variations and Long-Term Trends (2001-2018).

Tropospheric nitrogen dioxide (NO2) poses a serious threat to the environmental quality and public health. Satellite NO2 observations have been continuously used to monitor NO2 variations and improve model performances. However, the accuracy of satellite NO2 retrieval depends on the knowledge of aerosol optical properties, in particular for urban agglomerations accompanied by significant changes in aerosol characteristics. In this study, we investigate the impacts of aerosol composition on tropospheric NO2 retrieval for an 18 year global data set from Global Ozone Monitoring Experiment (GOME)-series satellite sensors. With a focus on cloud-free scenes dominated by the presence of aerosols, individual aerosol composition affects the uncertainties of tropospheric NO2 columns through impacts on the aerosol loading amount, relative vertical distribution of aerosol and NO2, aerosol absorption properties, and surface albedo determination. Among aerosol compositions, secondary inorganic aerosol mostly dominates the NO2 uncertainty by up to 43.5% in urban agglomerations, while organic aerosols contribute significantly to the NO2 uncertainty by -8.9 to 37.3% during biomass burning seasons. The possible contrary influences from different aerosol species highlight the importance and complexity of aerosol correction on tropospheric NO2 retrieval and indicate the need for a full picture of aerosol properties. This is of particular importance for interpreting seasonal variations or long-term trends of tropospheric NO2 columns as well as for mitigating ozone and fine particulate matter pollution.

MRI 3D SPACE T2WI for Pituitary Adenoma Cavernous Sinus Invasion Diagnosis.

OBJECTIVE: This study aims to assess the utility of magnetic resonance imaging (MRI) 3D SPACE T2-weighted imaging (T2WI) sequences in evaluating cavernous sinus invasion by pituitary adenomas. METHODS: Data were collected from patients who underwent continuous pituitary MRIexaminations at the Medical Imaging Center of our hospital from October 2019 to February 2021. Eligible cases were evaluated for sagittal and axial T1WI sequences, coronal 3D SPACE T2WI sequences, and sagittal and coronal enhanced T1-weighted imaging (T1WI) sequences using the INFINITT PACS workstation. The Wilcoxon signed-rank test for paired samples and the Mann-Whitney U test for 2 independent samples were used to statistically analyze differences in image quality scores among various groups. In addition, the sensitivity, specificity, positive predictive value, and negative predictive value of each observation index were compared with intraoperative results. RESULTS: 3D SPACE T2WI showed superior cavernous sinus imaging quality compared with contrast enhanced T1WI and T2WI plain scans (P < 0.05). The sensitivity, specificity, positive predictive value, and negative predictive value were 100%, 90.0%, 55.60%, and 100.0%, respectively. The accuracy for pituitary adenoma invasiveness diagnosis based on cavernous sinus medial wall integrity was 94.40%. CONCLUSIONS: The imaging quality of the medial wall of the cavernous sinus on the 3D SPACE T2WI plain scan sequence surpassed that of contrast enhanced T1WI TSE-enhanced scans and T2WI TSE plain scans. The continuous observation of the medial wall of the cavernous sinus using this sequence holds great diagnostic value for assessing cavernous sinus invasion by pituitary adenomas. This strategy is more reliable than traditional MRI observation indicators.

Molecularly-regulating oxygen-containing functional groups of ramie activated carbon for high-performance supercapacitors.

Effectively managing oxygen-containing functional groups (OCFGs) within activated carbon and methodically elucidating their intricate types and proportions are essential for considerably improving the electrochemical performance of carbon-based supercapacitors. Herein, we designed a ZnCl2-based molecular regulation strategy to introduce OCFGs into ramie-activated carbon (RAC), managing different OCFGs and revealing their structure-activity relationship with electrochemical performance. Thus, this regulated RAC, with a 3.5-fold enhancement in advantageous OCFGs (a-OCFGs: CO and COO), exhibits a supreme specific capacitance of 286.4F g-1 at 1 A/g and an excellent capacitance retention rate of 89.7 % at 20 A/g in an aqueous electrolyte, considerably surpassing that of nonregulated RAC (212.0F g-1 and 81.9 %). This confirms that a-OCFGs provide ample ion-storage accommodation and suppress solvent electronic oxidation, thereby enhancing electrochemical performance. Furthermore, its electrochemical performance is competitive with that of the commercial YP-50F (129.2F g-1 at 1 A/g). Therefore, this work not only highlights the contributions of specific OCFGs to high electrochemical performance but also designs a promising commercial electrode material to meet the demands of OCFGs-adequate carbon-based energy storage devices.

Association between ambient air pollutants and short-term mortality risks during 2015-2019 in Guangzhou, China.

With the development of technology and industry, the problem of global air pollution has become difficult to ignore. We investigated the association between air pollutant concentrations and daily all-cause mortality and stratified the analysis by sex, age, and season. Data for six air pollutants [fine particulate matter (PM2.5), inhalable particles (PM10), nitric dioxide (NO2), sulfur dioxide (SO2), ozone (O3), and carbon monoxide (CO)] and daily mortality rates were collected from 2015 to 2019 in Guangzhou, China. A time-series study using a quasi-Poisson generalized additive model was used to examine the relationships between environmental pollutant concentrations and mortality. Mortality data for 296,939 individuals were included in the analysis. The results showed that an increase of 10 µg/m3 in the concentrations of PM2.5, PM10, SO2, O3, NO2, and CO corresponded to 0.84% [95% confidence interval (CI): 0.47, 1.21%], 0.70% (0.44, 0.96%), 3.59% (1.77, 5.43%), 0.21% (0.05, 0.36%), 1.06% (0.70, 1.41%), and 0.05% (0.02, 0.09%), respectively. The effects of the six air pollutants were more significant for male individuals than female individuals, the cool season than the warm season, and people 75 years or older than those younger than 75 years. PM2.5, PM10, SO2, and NO2 were all associated with neoplasms and circulatory and respiratory diseases. The two-pollutant models found that PM2.5, PM10, and NO2 may independently affect the risk of mortality. The results showed that exposure to PM2.5, PM10 and NO2 may increase the risk of daily all-cause excessive mortality in Guangzhou.

Dynamic Transition between Monomer and Excimer Phosphorescence in Organic Near-Infrared Phosphorescent Crystals.

Achieving efficient near-infrared room-temperature phosphorescence of purely organic phosphors remains scarce and challenging due to strong nonradiative decay. Additionally, the investigation of triplet excimer phosphorescence is rarely reported, despite the fact that excimer, a special emitter commonly formed in crystals with strong π-π interactions, can efficiently change the fluorescent properties of compounds. Herein, a series of dithienopyrrole derivatives with low triplet energy levels and stable triplet states, exhibiting persistent near-infrared room-temperature phosphorescence, is developed. Via the modification of halogen atoms, the crystals display tunable emissions of monomers from 645 to 702 nm, with a maximum lifetime of 3.68 ms under ambient conditions. Notably, excimer phosphorescence can be switched on at low temperatures, enabled by noncovalent interactions rigidifying the matrix and stabilizing triplet excimer. Unprecedentedly, the dynamic transition process is captured between the monomer and excimer phosphorescence with temperature variations, revealing that the unstable triplet excimers in crystals with a tendency to dissociate can result in the effective quench of room-temperature phosphorescence. Excited state transitions across varying environments are elucidated, interpreting the structural dynamics of the triplet excimer and demonstrating strategies for devising novel near-infrared phosphors.

A sensitive lateral flow immunoassay relying on time-resolved fluorescent microspheres immune probe for determination of ceftiofur and its metabolite.

Ceftiofur (CEF) is an antimicrobial agent with high efficiency and low toxicity, desfuroylceftiofur is its main metabolite, but they are also have potential harm to human health. In this study, ceftiofur was combined with carrier proteins to get artificial antigens. A specific antibody (pAb) against CEF and desfuroylceftiofur was prepared. A sensitive and rapid paper-based sensor relying on time-resolved fluorescent microspheres (TRFMs) immune probes was developed, which were time-resolved fluorescent immunochromatographic strips (TRFMs-LFIA). The concentrations of T line and C line, activated pH, antibody volume and probe volume were optimized. Quantitative limits of detection (qLODs) of TRFMs-LFIA for CEF and desfuroylceftiofur were 0.97 ng/mL and 0.41 ng/mL, respectively. And 50 % inhibiting concentrations (IC50) were 12.92 ng/mL and 12.58 ng/mL, respectively. Pretreatment procedures of real samples were simple and rapid. Detection time of TRFMs-LFIA strip was 15 min. Qualitative analysis of CEF and desfuroylceftiofur was achieved under a UV light, quantitative analysis was implemented with a fluorescent immunoassay analyzer. The average recovery rates ranged from 91.4 % to 107.7 % and corresponding coefficients of variation (CV) was 1.5%-9.7 %. Concentration levels of artificially-spiked samples were measured by TRFMs-LFIA and compared with detection results of High performance liquid chromatography (HPLC), which showed a good accordance. These results indicated that the proposed assay can provide an effective strategy for on-site detection of CEF and desfuroylceftiofur simultaneously.

Self-Charging, Breathable, and Antibacterial Poly(lactic acid) Nanofibrous Air Filters by Surface Engineering of Ultrasmall Electroactive Nanohybrids.

Despite the great promise in the development of biodegradable and ecofriendly air filters by electrospinning of poly(lactic acid) (PLA) nanofibrous membranes (NFMs), the as-electrospun PLA nanofibers are generally characterized by poor electroactivity and smooth surface, challenging the exploitation of electrostatic adsorption and physical interception that are in need for efficient removal of pathogens and particulate matters (PMs). Herein, a combined "electrospinning-electrospray" strategy was disclosed to functionalize the PLA nanofibers by direct anchoring of highly dielectric BaTiO3@ZIF-8 nanohybrids (BTO@ZIF-8), conferring simultaneous promotion of surface roughness, electret properties (surface potential as high as 7.5 kV), and self-charging capability (∼190% increase in tribo-output voltage compared to that of pure PLA). Benefiting from the well-tailored morphology and increased electroactivity, the electrospun-electrosprayed PLA/BTO@ZIF-8 exhibited excellent PM-capturing performance (up to 96.54% for PM0.3 and 99.49% for PM2.5) while providing desirable air resistance (only 87 Pa at 32 L/min) due primarily to the slip flow of air molecules over the nanohybrid protrusions. This was accompanied by excellent antibacterial properties (99.9% inhibition against both Staphylococcus aureus and Escherichia coli), arising presumably from the synergistic effects of enhanced reactive oxygen species (ROS) generation, plentiful ion release, and surface charges. Our proposed strategy opens up pathways to afford exceptional combination of high-efficiency and low-resistance filtration, excellent antibacterial performance, and mechanical robustness without sacrificing the biodegradation profiles of PLA NFMs, holding potential implications for efficient and long-term healthcare.

Camera calibration using the dual double-contact property of circles.

To mitigate the influence of the relative positional relationship between circles on camera calibration, this study explores the double contact of dual circles with dual circular points. We demonstrate that one of the generalized eigenvectors of two dual circles corresponds to the line passing through their respective centers. Moreover, we establish a methodology to identify this line from the three generalized eigenvectors and show that, regardless of the positional arrangement of the three co-planar circles, the image of the circular points can be constructed by calculating the image of this line. Consequently, the applicability of circles as calibration templates is expanded, enabling the development of a novel optimization technique for fitting circular images with enhanced calibration precision.

Study of Pharmacokinetics for Ivermectin B1a from Beagle Dogs.

Ivermectin has been widely used for antiparasitic drug, and has recently shown a broad-spectrum antiviral activity, including anti-Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, the pharmacokinetic property of ivermectin has not been fully investigated yet. During the plasma preparation, ~32-46% of ivermectin was found in the precipitation. An Liquid Chromatograph-Mass Spectrometer (LC-MS/MS) method for ivermectin in the whole blood samples from beagle dogs was developed and validated. The specificity, accuracy, precision (intra-day and inter-day), matrix effect, recovery and stability of analyte reported here are satisfied with the criteria of Food and Drug Administration (FDA)-Bioanalysis guideline. The oral administrations pharmacokinetics of ivermectin in beagle dogs under fasting and after high-fat meal were studied, and the following parameters were obtained: fasting Cmax, 104 ± 35 µg·L-1; area under the concentration-time curve (AUC0-∞), 2,555 ± 941 h·µg·L-1; and high-fat meal Cmax, 147 ± 35 µg·L-1; AUC0-∞, 4,198 ± 1,279 h·µg·L-1. When the P-gp inhibitor curcumin was also coadministrated orally, Cmax and AUC0-∞ were found to be 177 ± 57 and 4,213 ± 948 h·µg·L-1, respectively. With the comparison to fasting treatment, coadministration of P-gp inhibitor curcumin resulted in increase of the exposure of ivermectin by 1.6-fold, while the exposure after the high-fat diet versus fasting was increased approximately in 1.4-fold, indicating that alternative absorption might play an important role for increasing the exposure of ivermectin for future clinic applications.